diff --git a/Sounak97.ipynb b/Sounak97.ipynb
new file mode 100644
index 0000000..5604dc2
--- /dev/null
+++ b/Sounak97.ipynb
@@ -0,0 +1,9533 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Sounak97.ipynb",
+      "version": "0.3.2",
+      "provenance": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "[View in Colaboratory](https://colab.research.google.com/github/Sounak97/Assignment-4/blob/Sounak97/Sounak97.ipynb)"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "9PagdA52jTCC",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "import numpy as np\n",
+        "import tensorflow as tf\n",
+        "import matplotlib.pyplot as plt"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "7amWGEh7kZDu",
+        "colab_type": "text"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "Linear Regression"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "2uLabDshkeEY",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "# Creating the dataset\n",
+        "X = np.linspace(-30.0, 300.0, 300)\n",
+        "Y = 2 * np.linspace(-30.0, 250.0, 300) + np.random.randn(*X.shape)\n",
+        "\n",
+        "# Dividing it into train and test\n",
+        "train_X = X[:250]\n",
+        "train_Y = Y[:250]\n",
+        "\n",
+        "test_X = X[250:]\n",
+        "test_Y = Y[250:]"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "TQ-Y26Dnklgg",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "learning_rate = 0.000005\n",
+        "n_epochs = 1000\n",
+        "interval = 50"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "7nba9_srkpWv",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 347
+        },
+        "outputId": "fb01c749-7211-4bd9-bd2d-d495c3229814"
+      },
+      "cell_type": "code",
+      "source": [
+        "plt.plot(train_X[:10], train_Y[:10], 'g')\n",
+        "plt.show()"
+      ],
+      "execution_count": 8,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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+Dl+nO9Ici86ZZ3j28hkeXxnFjrQf6Fb7Ht7s9p7TXkfcmefoSjRHx3DEHIOD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\nAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe5842512e8>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "yxjy1TMsks48",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "#placeholders used to hold defined values since we cannot use constants\n",
+        "x = tf.placeholder(tf.float32, name='x')\n",
+        "y = tf.placeholder(tf.float32, name='y')"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "jWPLHbynlCR_",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "W = tf.Variable(0.0, name='weight_1')\n",
+        "b = tf.Variable(0.0, name='bias_1')\n",
+        "\n",
+        "pred_y = (W*x) + b"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "a44bSV7nlIiF",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "loss = tf.reduce_mean(tf.square(y - pred_y))#using the mean aquared loss"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "g9QR1_ijlRhG",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate).minimize(loss)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "jQ59qSd6lZKZ",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 717
+        },
+        "outputId": "9064ba08-d590-4425-8a5b-26f57e244a6c"
+      },
+      "cell_type": "code",
+      "source": [
+        "#training the model and getting an output\n",
+        "with tf.Session() as sess:\n",
+        "  sess.run(tf.global_variables_initializer())\n",
+        "  \n",
+        "  for epoch in range(n_epochs):\n",
+        "    _, curr_loss = sess.run([optimizer, loss], feed_dict={x:train_X, y:train_Y})\n",
+        "    \n",
+        "    if epoch % interval == 0:\n",
+        "      print ('Loss after epoch', epoch, ' is ', curr_loss)\n",
+        "    \n",
+        "  print ('Now testing the model in the test set')\n",
+        "  final_preds, final_loss = sess.run([pred_y, loss], feed_dict={x:test_X, y:test_Y})\n",
+        "    \n",
+        "  print ('The final loss is: ', final_loss)\n",
+        "  plt.plot(test_X[:10], test_Y[:10], 'g', label='True Function')\n",
+        "  plt.plot(test_X[:10], final_preds[:10], 'r', label='Predicted Function')\n",
+        "  plt.legend()\n",
+        "  plt.show()"
+      ],
+      "execution_count": 14,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0  is  48307.223\n",
+            "Loss after epoch 50  is  30.787357\n",
+            "Loss after epoch 100  is  30.77665\n",
+            "Loss after epoch 150  is  30.766047\n",
+            "Loss after epoch 200  is  30.755514\n",
+            "Loss after epoch 250  is  30.744925\n",
+            "Loss after epoch 300  is  30.734344\n",
+            "Loss after epoch 350  is  30.72381\n",
+            "Loss after epoch 400  is  30.713232\n",
+            "Loss after epoch 450  is  30.702675\n",
+            "Loss after epoch 500  is  30.69212\n",
+            "Loss after epoch 550  is  30.681557\n",
+            "Loss after epoch 600  is  30.671059\n",
+            "Loss after epoch 650  is  30.66049\n",
+            "Loss after epoch 700  is  30.649956\n",
+            "Loss after epoch 750  is  30.639421\n",
+            "Loss after epoch 800  is  30.628874\n",
+            "Loss after epoch 850  is  30.618353\n",
+            "Loss after epoch 900  is  30.60786\n",
+            "Loss after epoch 950  is  30.597326\n",
+            "Now testing the model in the test set\n",
+            "The final loss is:  32.656258\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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CiGKXac2k66rO/H5uD73rP0dSq5loNbI5wa0y/LwBc3wshm1bUbRa8nr1wTps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\nUgAHmYiISAEcZCIiIgVwkImIiBTwPzcl6cSi33U7AAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe581a20eb8>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "eSppqPw0lv-k",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        "def linear_regression(learning_rate,n_epochs,interval):\n",
+        "  x=tf.placeholder(tf.float32,name='x')\n",
+        "  y=tf.placeholder(tf.float32,name='y')\n",
+        "  W=tf.Variable(0.0,name='weight_1')\n",
+        "  b=tf.Variable(0.0,name='bias_1')\n",
+        "  pred_y=(W*x)+b\n",
+        "  loss=tf.reduce_mean(tf.square(y-pred_y))\n",
+        "  optimizer=tf.train.GradientDescentOptimizer(learning_rate=learning_rate).minimize(loss)\n",
+        "  with tf.Session() as sess:\n",
+        "    sess.run(tf.global_variables_initializer())\n",
+        "    for epoch in range(n_epochs):\n",
+        "      _,curr_loss=sess.run([optimizer,loss],feed_dict={x:train_X,y:train_Y})\n",
+        "      if epoch % interval==0:\n",
+        "        print('Loss after epoch',epoch,'is',curr_loss)\n",
+        "    print('Now testing the model in the test set')\n",
+        "    final_preds,final_loss=sess.run([pred_y,loss],feed_dict={x:test_X,y:test_Y})\n",
+        "    print('The final loss is:',final_loss)\n",
+        "    #plotting\n",
+        "    plt.plot(test_X[:10],test_Y[:10],'g',label='True function')\n",
+        "    plt.plot(test_X[:10],final_preds[:10],'r',label='Predicted Function')\n",
+        "    plt.legend()\n",
+        "    plt.show()\n",
+        "    \n",
+        "pass\n"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "qi1WOC7ksINC",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 2061
+        },
+        "outputId": "2da9c8a1-8bff-4396-9223-64e99c01d654"
+      },
+      "cell_type": "code",
+      "source": [
+        "#Tweaking\n",
+        "linear_regression(learning_rate=0.00003,n_epochs=5000,interval=50)"
+      ],
+      "execution_count": 22,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.734344\n",
+            "Loss after epoch 100 is 30.671047\n",
+            "Loss after epoch 150 is 30.607859\n",
+            "Loss after epoch 200 is 30.544771\n",
+            "Loss after epoch 250 is 30.481882\n",
+            "Loss after epoch 300 is 30.419096\n",
+            "Loss after epoch 350 is 30.356417\n",
+            "Loss after epoch 400 is 30.293922\n",
+            "Loss after epoch 450 is 30.23153\n",
+            "Loss after epoch 500 is 30.169252\n",
+            "Loss after epoch 550 is 30.107166\n",
+            "Loss after epoch 600 is 30.045181\n",
+            "Loss after epoch 650 is 29.9833\n",
+            "Loss after epoch 700 is 29.92155\n",
+            "Loss after epoch 750 is 29.859951\n",
+            "Loss after epoch 800 is 29.79851\n",
+            "Loss after epoch 850 is 29.737165\n",
+            "Loss after epoch 900 is 29.67596\n",
+            "Loss after epoch 950 is 29.614902\n",
+            "Loss after epoch 1000 is 29.55394\n",
+            "Loss after epoch 1050 is 29.493147\n",
+            "Loss after epoch 1100 is 29.432467\n",
+            "Loss after epoch 1150 is 29.371904\n",
+            "Loss after epoch 1200 is 29.311493\n",
+            "Loss after epoch 1250 is 29.251202\n",
+            "Loss after epoch 1300 is 29.19102\n",
+            "Loss after epoch 1350 is 29.130974\n",
+            "Loss after epoch 1400 is 29.071066\n",
+            "Loss after epoch 1450 is 29.011265\n",
+            "Loss after epoch 1500 is 28.951609\n",
+            "Loss after epoch 1550 is 28.892097\n",
+            "Loss after epoch 1600 is 28.832668\n",
+            "Loss after epoch 1650 is 28.773388\n",
+            "Loss after epoch 1700 is 28.71426\n",
+            "Loss after epoch 1750 is 28.655216\n",
+            "Loss after epoch 1800 is 28.596312\n",
+            "Loss after epoch 1850 is 28.537556\n",
+            "Loss after epoch 1900 is 28.478874\n",
+            "Loss after epoch 1950 is 28.420351\n",
+            "Loss after epoch 2000 is 28.361973\n",
+            "Loss after epoch 2050 is 28.303669\n",
+            "Loss after epoch 2100 is 28.245522\n",
+            "Loss after epoch 2150 is 28.187506\n",
+            "Loss after epoch 2200 is 28.129576\n",
+            "Loss after epoch 2250 is 28.07179\n",
+            "Loss after epoch 2300 is 28.014128\n",
+            "Loss after epoch 2350 is 27.956577\n",
+            "Loss after epoch 2400 is 27.899157\n",
+            "Loss after epoch 2450 is 27.84188\n",
+            "Loss after epoch 2500 is 27.784727\n",
+            "Loss after epoch 2550 is 27.727663\n",
+            "Loss after epoch 2600 is 27.67075\n",
+            "Loss after epoch 2650 is 27.613924\n",
+            "Loss after epoch 2700 is 27.557236\n",
+            "Loss after epoch 2750 is 27.500666\n",
+            "Loss after epoch 2800 is 27.444239\n",
+            "Loss after epoch 2850 is 27.38789\n",
+            "Loss after epoch 2900 is 27.3317\n",
+            "Loss after epoch 2950 is 27.275599\n",
+            "Loss after epoch 3000 is 27.219606\n",
+            "Loss after epoch 3050 is 27.16376\n",
+            "Loss after epoch 3100 is 27.108044\n",
+            "Loss after epoch 3150 is 27.052437\n",
+            "Loss after epoch 3200 is 26.996937\n",
+            "Loss after epoch 3250 is 26.94157\n",
+            "Loss after epoch 3300 is 26.886305\n",
+            "Loss after epoch 3350 is 26.831167\n",
+            "Loss after epoch 3400 is 26.77615\n",
+            "Loss after epoch 3450 is 26.721237\n",
+            "Loss after epoch 3500 is 26.666435\n",
+            "Loss after epoch 3550 is 26.611782\n",
+            "Loss after epoch 3600 is 26.557196\n",
+            "Loss after epoch 3650 is 26.502794\n",
+            "Loss after epoch 3700 is 26.44844\n",
+            "Loss after epoch 3750 is 26.394245\n",
+            "Loss after epoch 3800 is 26.34015\n",
+            "Loss after epoch 3850 is 26.286171\n",
+            "Loss after epoch 3900 is 26.232286\n",
+            "Loss after epoch 3950 is 26.178577\n",
+            "Loss after epoch 4000 is 26.12494\n",
+            "Loss after epoch 4050 is 26.071396\n",
+            "Loss after epoch 4100 is 26.017971\n",
+            "Loss after epoch 4150 is 25.96468\n",
+            "Loss after epoch 4200 is 25.911524\n",
+            "Loss after epoch 4250 is 25.858427\n",
+            "Loss after epoch 4300 is 25.805473\n",
+            "Loss after epoch 4350 is 25.752653\n",
+            "Loss after epoch 4400 is 25.699942\n",
+            "Loss after epoch 4450 is 25.64732\n",
+            "Loss after epoch 4500 is 25.5948\n",
+            "Loss after epoch 4550 is 25.542402\n",
+            "Loss after epoch 4600 is 25.490124\n",
+            "Loss after epoch 4650 is 25.437956\n",
+            "Loss after epoch 4700 is 25.385908\n",
+            "Loss after epoch 4750 is 25.333939\n",
+            "Loss after epoch 4800 is 25.2821\n",
+            "Loss after epoch 4850 is 25.230352\n",
+            "Loss after epoch 4900 is 25.178757\n",
+            "Loss after epoch 4950 is 25.12724\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 26.495762\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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meX56XAghirLYK3sIXP8St9Nu8U69IYxqPBYXvYvasYq29HSclyzEOCMC7bUE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\nAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e700208>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "5xHvnd7XsdhR",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 8781
+        },
+        "outputId": "6484a600-9b5d-4c2c-cad3-46382dce3b56"
+      },
+      "cell_type": "code",
+      "source": [
+        "#driving loss to minimum\n",
+        "linear_regression(learning_rate=0.00002,n_epochs=5000,interval=10)"
+      ],
+      "execution_count": 23,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 10 is 30.789343\n",
+            "Loss after epoch 20 is 30.78088\n",
+            "Loss after epoch 30 is 30.772398\n",
+            "Loss after epoch 40 is 30.763958\n",
+            "Loss after epoch 50 is 30.75551\n",
+            "Loss after epoch 60 is 30.747015\n",
+            "Loss after epoch 70 is 30.738585\n",
+            "Loss after epoch 80 is 30.730152\n",
+            "Loss after epoch 90 is 30.72168\n",
+            "Loss after epoch 100 is 30.71323\n",
+            "Loss after epoch 110 is 30.70477\n",
+            "Loss after epoch 120 is 30.696346\n",
+            "Loss after epoch 130 is 30.68789\n",
+            "Loss after epoch 140 is 30.679466\n",
+            "Loss after epoch 150 is 30.671059\n",
+            "Loss after epoch 160 is 30.662601\n",
+            "Loss after epoch 170 is 30.654186\n",
+            "Loss after epoch 180 is 30.645727\n",
+            "Loss after epoch 190 is 30.63732\n",
+            "Loss after epoch 200 is 30.628878\n",
+            "Loss after epoch 210 is 30.620472\n",
+            "Loss after epoch 220 is 30.612028\n",
+            "Loss after epoch 230 is 30.603628\n",
+            "Loss after epoch 240 is 30.595198\n",
+            "Loss after epoch 250 is 30.586803\n",
+            "Loss after epoch 260 is 30.578377\n",
+            "Loss after epoch 270 is 30.569992\n",
+            "Loss after epoch 280 is 30.56158\n",
+            "Loss after epoch 290 is 30.553192\n",
+            "Loss after epoch 300 is 30.544779\n",
+            "Loss after epoch 310 is 30.536396\n",
+            "Loss after epoch 320 is 30.527996\n",
+            "Loss after epoch 330 is 30.519625\n",
+            "Loss after epoch 340 is 30.511213\n",
+            "Loss after epoch 350 is 30.502848\n",
+            "Loss after epoch 360 is 30.494444\n",
+            "Loss after epoch 370 is 30.486038\n",
+            "Loss after epoch 380 is 30.477676\n",
+            "Loss after epoch 390 is 30.469273\n",
+            "Loss after epoch 400 is 30.460943\n",
+            "Loss after epoch 410 is 30.452559\n",
+            "Loss after epoch 420 is 30.44416\n",
+            "Loss after epoch 430 is 30.435808\n",
+            "Loss after epoch 440 is 30.427425\n",
+            "Loss after epoch 450 is 30.419096\n",
+            "Loss after epoch 460 is 30.410723\n",
+            "Loss after epoch 470 is 30.40234\n",
+            "Loss after epoch 480 is 30.394026\n",
+            "Loss after epoch 490 is 30.385654\n",
+            "Loss after epoch 500 is 30.377275\n",
+            "Loss after epoch 510 is 30.368952\n",
+            "Loss after epoch 520 is 30.3606\n",
+            "Loss after epoch 530 is 30.352234\n",
+            "Loss after epoch 540 is 30.343914\n",
+            "Loss after epoch 550 is 30.335577\n",
+            "Loss after epoch 560 is 30.327217\n",
+            "Loss after epoch 570 is 30.318918\n",
+            "Loss after epoch 580 is 30.31057\n",
+            "Loss after epoch 590 is 30.302221\n",
+            "Loss after epoch 600 is 30.293936\n",
+            "Loss after epoch 610 is 30.285583\n",
+            "Loss after epoch 620 is 30.277266\n",
+            "Loss after epoch 630 is 30.268915\n",
+            "Loss after epoch 640 is 30.26064\n",
+            "Loss after epoch 650 is 30.252296\n",
+            "Loss after epoch 660 is 30.24399\n",
+            "Loss after epoch 670 is 30.235655\n",
+            "Loss after epoch 680 is 30.227383\n",
+            "Loss after epoch 690 is 30.219057\n",
+            "Loss after epoch 700 is 30.210756\n",
+            "Loss after epoch 710 is 30.202435\n",
+            "Loss after epoch 720 is 30.194172\n",
+            "Loss after epoch 730 is 30.18586\n",
+            "Loss after epoch 740 is 30.177568\n",
+            "Loss after epoch 750 is 30.169273\n",
+            "Loss after epoch 760 is 30.160954\n",
+            "Loss after epoch 770 is 30.152706\n",
+            "Loss after epoch 780 is 30.144402\n",
+            "Loss after epoch 790 is 30.13612\n",
+            "Loss after epoch 800 is 30.127838\n",
+            "Loss after epoch 810 is 30.119541\n",
+            "Loss after epoch 820 is 30.111267\n",
+            "Loss after epoch 830 is 30.103024\n",
+            "Loss after epoch 840 is 30.09474\n",
+            "Loss after epoch 850 is 30.086468\n",
+            "Loss after epoch 860 is 30.078207\n",
+            "Loss after epoch 870 is 30.069937\n",
+            "Loss after epoch 880 is 30.06166\n",
+            "Loss after epoch 890 is 30.053396\n",
+            "Loss after epoch 900 is 30.045185\n",
+            "Loss after epoch 910 is 30.036915\n",
+            "Loss after epoch 920 is 30.028667\n",
+            "Loss after epoch 930 is 30.020403\n",
+            "Loss after epoch 940 is 30.012142\n",
+            "Loss after epoch 950 is 30.003904\n",
+            "Loss after epoch 960 is 29.99566\n",
+            "Loss after epoch 970 is 29.987417\n",
+            "Loss after epoch 980 is 29.979176\n",
+            "Loss after epoch 990 is 29.970926\n",
+            "Loss after epoch 1000 is 29.962696\n",
+            "Loss after epoch 1010 is 29.954458\n",
+            "Loss after epoch 1020 is 29.946224\n",
+            "Loss after epoch 1030 is 29.938002\n",
+            "Loss after epoch 1040 is 29.929771\n",
+            "Loss after epoch 1050 is 29.921555\n",
+            "Loss after epoch 1060 is 29.91334\n",
+            "Loss after epoch 1070 is 29.905117\n",
+            "Loss after epoch 1080 is 29.896898\n",
+            "Loss after epoch 1090 is 29.888687\n",
+            "Loss after epoch 1100 is 29.880474\n",
+            "Loss after epoch 1110 is 29.872267\n",
+            "Loss after epoch 1120 is 29.864061\n",
+            "Loss after epoch 1130 is 29.855854\n",
+            "Loss after epoch 1140 is 29.847654\n",
+            "Loss after epoch 1150 is 29.839466\n",
+            "Loss after epoch 1160 is 29.831266\n",
+            "Loss after epoch 1170 is 29.823084\n",
+            "Loss after epoch 1180 is 29.814888\n",
+            "Loss after epoch 1190 is 29.806698\n",
+            "Loss after epoch 1200 is 29.79852\n",
+            "Loss after epoch 1210 is 29.79033\n",
+            "Loss after epoch 1220 is 29.782145\n",
+            "Loss after epoch 1230 is 29.77397\n",
+            "Loss after epoch 1240 is 29.765802\n",
+            "Loss after epoch 1250 is 29.757626\n",
+            "Loss after epoch 1260 is 29.749454\n",
+            "Loss after epoch 1270 is 29.741245\n",
+            "Loss after epoch 1280 is 29.733082\n",
+            "Loss after epoch 1290 is 29.72493\n",
+            "Loss after epoch 1300 is 29.71677\n",
+            "Loss after epoch 1310 is 29.708601\n",
+            "Loss after epoch 1320 is 29.700443\n",
+            "Loss after epoch 1330 is 29.692299\n",
+            "Loss after epoch 1340 is 29.684109\n",
+            "Loss after epoch 1350 is 29.675962\n",
+            "Loss after epoch 1360 is 29.667824\n",
+            "Loss after epoch 1370 is 29.65968\n",
+            "Loss after epoch 1380 is 29.651539\n",
+            "Loss after epoch 1390 is 29.643408\n",
+            "Loss after epoch 1400 is 29.635223\n",
+            "Loss after epoch 1410 is 29.627113\n",
+            "Loss after epoch 1420 is 29.618979\n",
+            "Loss after epoch 1430 is 29.610844\n",
+            "Loss after epoch 1440 is 29.602722\n",
+            "Loss after epoch 1450 is 29.594557\n",
+            "Loss after epoch 1460 is 29.586441\n",
+            "Loss after epoch 1470 is 29.578323\n",
+            "Loss after epoch 1480 is 29.570219\n",
+            "Loss after epoch 1490 is 29.562067\n",
+            "Loss after epoch 1500 is 29.55396\n",
+            "Loss after epoch 1510 is 29.54584\n",
+            "Loss after epoch 1520 is 29.537746\n",
+            "Loss after epoch 1530 is 29.529602\n",
+            "Loss after epoch 1540 is 29.521507\n",
+            "Loss after epoch 1550 is 29.513403\n",
+            "Loss after epoch 1560 is 29.50532\n",
+            "Loss after epoch 1570 is 29.497187\n",
+            "Loss after epoch 1580 is 29.489103\n",
+            "Loss after epoch 1590 is 29.48102\n",
+            "Loss after epoch 1600 is 29.472883\n",
+            "Loss after epoch 1610 is 29.464802\n",
+            "Loss after epoch 1620 is 29.45673\n",
+            "Loss after epoch 1630 is 29.448616\n",
+            "Loss after epoch 1640 is 29.440548\n",
+            "Loss after epoch 1650 is 29.432465\n",
+            "Loss after epoch 1660 is 29.424364\n",
+            "Loss after epoch 1670 is 29.416304\n",
+            "Loss after epoch 1680 is 29.40823\n",
+            "Loss after epoch 1690 is 29.400135\n",
+            "Loss after epoch 1700 is 29.392094\n",
+            "Loss after epoch 1710 is 29.38403\n",
+            "Loss after epoch 1720 is 29.375927\n",
+            "Loss after epoch 1730 is 29.367868\n",
+            "Loss after epoch 1740 is 29.359835\n",
+            "Loss after epoch 1750 is 29.351751\n",
+            "Loss after epoch 1760 is 29.34372\n",
+            "Loss after epoch 1770 is 29.335623\n",
+            "Loss after epoch 1780 is 29.327581\n",
+            "Loss after epoch 1790 is 29.31955\n",
+            "Loss after epoch 1800 is 29.311497\n",
+            "Loss after epoch 1810 is 29.303455\n",
+            "Loss after epoch 1820 is 29.295395\n",
+            "Loss after epoch 1830 is 29.287352\n",
+            "Loss after epoch 1840 is 29.279291\n",
+            "Loss after epoch 1850 is 29.271275\n",
+            "Loss after epoch 1860 is 29.263214\n",
+            "Loss after epoch 1870 is 29.255198\n",
+            "Loss after epoch 1880 is 29.247147\n",
+            "Loss after epoch 1890 is 29.239145\n",
+            "Loss after epoch 1900 is 29.23113\n",
+            "Loss after epoch 1910 is 29.223097\n",
+            "Loss after epoch 1920 is 29.215094\n",
+            "Loss after epoch 1930 is 29.207056\n",
+            "Loss after epoch 1940 is 29.19905\n",
+            "Loss after epoch 1950 is 29.19102\n",
+            "Loss after epoch 1960 is 29.182987\n",
+            "Loss after epoch 1970 is 29.174992\n",
+            "Loss after epoch 1980 is 29.16697\n",
+            "Loss after epoch 1990 is 29.158981\n",
+            "Loss after epoch 2000 is 29.150959\n",
+            "Loss after epoch 2010 is 29.142979\n",
+            "Loss after epoch 2020 is 29.13496\n",
+            "Loss after epoch 2030 is 29.126995\n",
+            "Loss after epoch 2040 is 29.118977\n",
+            "Loss after epoch 2050 is 29.111013\n",
+            "Loss after epoch 2060 is 29.102999\n",
+            "Loss after epoch 2070 is 29.094994\n",
+            "Loss after epoch 2080 is 29.087034\n",
+            "Loss after epoch 2090 is 29.079042\n",
+            "Loss after epoch 2100 is 29.071081\n",
+            "Loss after epoch 2110 is 29.063082\n",
+            "Loss after epoch 2120 is 29.055086\n",
+            "Loss after epoch 2130 is 29.047134\n",
+            "Loss after epoch 2140 is 29.03916\n",
+            "Loss after epoch 2150 is 29.031212\n",
+            "Loss after epoch 2160 is 29.023216\n",
+            "Loss after epoch 2170 is 29.015257\n",
+            "Loss after epoch 2180 is 29.00732\n",
+            "Loss after epoch 2190 is 28.999336\n",
+            "Loss after epoch 2200 is 28.99136\n",
+            "Loss after epoch 2210 is 28.983444\n",
+            "Loss after epoch 2220 is 28.975454\n",
+            "Loss after epoch 2230 is 28.967499\n",
+            "Loss after epoch 2240 is 28.959583\n",
+            "Loss after epoch 2250 is 28.951612\n",
+            "Loss after epoch 2260 is 28.94367\n",
+            "Loss after epoch 2270 is 28.935713\n",
+            "Loss after epoch 2280 is 28.927795\n",
+            "Loss after epoch 2290 is 28.919853\n",
+            "Loss after epoch 2300 is 28.911898\n",
+            "Loss after epoch 2310 is 28.903996\n",
+            "Loss after epoch 2320 is 28.896048\n",
+            "Loss after epoch 2330 is 28.888123\n",
+            "Loss after epoch 2340 is 28.880175\n",
+            "Loss after epoch 2350 is 28.872288\n",
+            "Loss after epoch 2360 is 28.864346\n",
+            "Loss after epoch 2370 is 28.856426\n",
+            "Loss after epoch 2380 is 28.848488\n",
+            "Loss after epoch 2390 is 28.840601\n",
+            "Loss after epoch 2400 is 28.832682\n",
+            "Loss after epoch 2410 is 28.824774\n",
+            "Loss after epoch 2420 is 28.816843\n",
+            "Loss after epoch 2430 is 28.80893\n",
+            "Loss after epoch 2440 is 28.801058\n",
+            "Loss after epoch 2450 is 28.793137\n",
+            "Loss after epoch 2460 is 28.78525\n",
+            "Loss after epoch 2470 is 28.777327\n",
+            "Loss after epoch 2480 is 28.769432\n",
+            "Loss after epoch 2490 is 28.761578\n",
+            "Loss after epoch 2500 is 28.753666\n",
+            "Loss after epoch 2510 is 28.745777\n",
+            "Loss after epoch 2520 is 28.737883\n",
+            "Loss after epoch 2530 is 28.730005\n",
+            "Loss after epoch 2540 is 28.722113\n",
+            "Loss after epoch 2550 is 28.714226\n",
+            "Loss after epoch 2560 is 28.706383\n",
+            "Loss after epoch 2570 is 28.698492\n",
+            "Loss after epoch 2580 is 28.690624\n",
+            "Loss after epoch 2590 is 28.682745\n",
+            "Loss after epoch 2600 is 28.674885\n",
+            "Loss after epoch 2610 is 28.66701\n",
+            "Loss after epoch 2620 is 28.659132\n",
+            "Loss after epoch 2630 is 28.651274\n",
+            "Loss after epoch 2640 is 28.643404\n",
+            "Loss after epoch 2650 is 28.635593\n",
+            "Loss after epoch 2660 is 28.627737\n",
+            "Loss after epoch 2670 is 28.619883\n",
+            "Loss after epoch 2680 is 28.61203\n",
+            "Loss after epoch 2690 is 28.604162\n",
+            "Loss after epoch 2700 is 28.596317\n",
+            "Loss after epoch 2710 is 28.588472\n",
+            "Loss after epoch 2720 is 28.580631\n",
+            "Loss after epoch 2730 is 28.572784\n",
+            "Loss after epoch 2740 is 28.564959\n",
+            "Loss after epoch 2750 is 28.557116\n",
+            "Loss after epoch 2760 is 28.549284\n",
+            "Loss after epoch 2770 is 28.541454\n",
+            "Loss after epoch 2780 is 28.533628\n",
+            "Loss after epoch 2790 is 28.5258\n",
+            "Loss after epoch 2800 is 28.517973\n",
+            "Loss after epoch 2810 is 28.510149\n",
+            "Loss after epoch 2820 is 28.50233\n",
+            "Loss after epoch 2830 is 28.494516\n",
+            "Loss after epoch 2840 is 28.4867\n",
+            "Loss after epoch 2850 is 28.478893\n",
+            "Loss after epoch 2860 is 28.471085\n",
+            "Loss after epoch 2870 is 28.463272\n",
+            "Loss after epoch 2880 is 28.45548\n",
+            "Loss after epoch 2890 is 28.447674\n",
+            "Loss after epoch 2900 is 28.439875\n",
+            "Loss after epoch 2910 is 28.432037\n",
+            "Loss after epoch 2920 is 28.42424\n",
+            "Loss after epoch 2930 is 28.416449\n",
+            "Loss after epoch 2940 is 28.408672\n",
+            "Loss after epoch 2950 is 28.400875\n",
+            "Loss after epoch 2960 is 28.393093\n",
+            "Loss after epoch 2970 is 28.38531\n",
+            "Loss after epoch 2980 is 28.377523\n",
+            "Loss after epoch 2990 is 28.369753\n",
+            "Loss after epoch 3000 is 28.361979\n",
+            "Loss after epoch 3010 is 28.354162\n",
+            "Loss after epoch 3020 is 28.346392\n",
+            "Loss after epoch 3030 is 28.338634\n",
+            "Loss after epoch 3040 is 28.330862\n",
+            "Loss after epoch 3050 is 28.323093\n",
+            "Loss after epoch 3060 is 28.31534\n",
+            "Loss after epoch 3070 is 28.307583\n",
+            "Loss after epoch 3080 is 28.299788\n",
+            "Loss after epoch 3090 is 28.292042\n",
+            "Loss after epoch 3100 is 28.284277\n",
+            "Loss after epoch 3110 is 28.276531\n",
+            "Loss after epoch 3120 is 28.268791\n",
+            "Loss after epoch 3130 is 28.261002\n",
+            "Loss after epoch 3140 is 28.25327\n",
+            "Loss after epoch 3150 is 28.245523\n",
+            "Loss after epoch 3160 is 28.237785\n",
+            "Loss after epoch 3170 is 28.230062\n",
+            "Loss after epoch 3180 is 28.222284\n",
+            "Loss after epoch 3190 is 28.214563\n",
+            "Loss after epoch 3200 is 28.20683\n",
+            "Loss after epoch 3210 is 28.19911\n",
+            "Loss after epoch 3220 is 28.191349\n",
+            "Loss after epoch 3230 is 28.18363\n",
+            "Loss after epoch 3240 is 28.175905\n",
+            "Loss after epoch 3250 is 28.168201\n",
+            "Loss after epoch 3260 is 28.160461\n",
+            "Loss after epoch 3270 is 28.152737\n",
+            "Loss after epoch 3280 is 28.145033\n",
+            "Loss after epoch 3290 is 28.13728\n",
+            "Loss after epoch 3300 is 28.129593\n",
+            "Loss after epoch 3310 is 28.121878\n",
+            "Loss after epoch 3320 is 28.114147\n",
+            "Loss after epoch 3330 is 28.106459\n",
+            "Loss after epoch 3340 is 28.098757\n",
+            "Loss after epoch 3350 is 28.091032\n",
+            "Loss after epoch 3360 is 28.083353\n",
+            "Loss after epoch 3370 is 28.075653\n",
+            "Loss after epoch 3380 is 28.067934\n",
+            "Loss after epoch 3390 is 28.060272\n",
+            "Loss after epoch 3400 is 28.05257\n",
+            "Loss after epoch 3410 is 28.044859\n",
+            "Loss after epoch 3420 is 28.037195\n",
+            "Loss after epoch 3430 is 28.029522\n",
+            "Loss after epoch 3440 is 28.02181\n",
+            "Loss after epoch 3450 is 28.014137\n",
+            "Loss after epoch 3460 is 28.006447\n",
+            "Loss after epoch 3470 is 27.99879\n",
+            "Loss after epoch 3480 is 27.991129\n",
+            "Loss after epoch 3490 is 27.983425\n",
+            "Loss after epoch 3500 is 27.975775\n",
+            "Loss after epoch 3510 is 27.968084\n",
+            "Loss after epoch 3520 is 27.96044\n",
+            "Loss after epoch 3530 is 27.952793\n",
+            "Loss after epoch 3540 is 27.94511\n",
+            "Loss after epoch 3550 is 27.93747\n",
+            "Loss after epoch 3560 is 27.929777\n",
+            "Loss after epoch 3570 is 27.92214\n",
+            "Loss after epoch 3580 is 27.914473\n",
+            "Loss after epoch 3590 is 27.906841\n",
+            "Loss after epoch 3600 is 27.899168\n",
+            "Loss after epoch 3610 is 27.891535\n",
+            "Loss after epoch 3620 is 27.883875\n",
+            "Loss after epoch 3630 is 27.876251\n",
+            "Loss after epoch 3640 is 27.868591\n",
+            "Loss after epoch 3650 is 27.860973\n",
+            "Loss after epoch 3660 is 27.853321\n",
+            "Loss after epoch 3670 is 27.84571\n",
+            "Loss after epoch 3680 is 27.838055\n",
+            "Loss after epoch 3690 is 27.83044\n",
+            "Loss after epoch 3700 is 27.82281\n",
+            "Loss after epoch 3710 is 27.815199\n",
+            "Loss after epoch 3720 is 27.80756\n",
+            "Loss after epoch 3730 is 27.79997\n",
+            "Loss after epoch 3740 is 27.792332\n",
+            "Loss after epoch 3750 is 27.784742\n",
+            "Loss after epoch 3760 is 27.777117\n",
+            "Loss after epoch 3770 is 27.769476\n",
+            "Loss after epoch 3780 is 27.761885\n",
+            "Loss after epoch 3790 is 27.75426\n",
+            "Loss after epoch 3800 is 27.746689\n",
+            "Loss after epoch 3810 is 27.739067\n",
+            "Loss after epoch 3820 is 27.731493\n",
+            "Loss after epoch 3830 is 27.723871\n",
+            "Loss after epoch 3840 is 27.716257\n",
+            "Loss after epoch 3850 is 27.708694\n",
+            "Loss after epoch 3860 is 27.70109\n",
+            "Loss after epoch 3870 is 27.693476\n",
+            "Loss after epoch 3880 is 27.68591\n",
+            "Loss after epoch 3890 is 27.678322\n",
+            "Loss after epoch 3900 is 27.67076\n",
+            "Loss after epoch 3910 is 27.663153\n",
+            "Loss after epoch 3920 is 27.655577\n",
+            "Loss after epoch 3930 is 27.648022\n",
+            "Loss after epoch 3940 is 27.640427\n",
+            "Loss after epoch 3950 is 27.632856\n",
+            "Loss after epoch 3960 is 27.625307\n",
+            "Loss after epoch 3970 is 27.617722\n",
+            "Loss after epoch 3980 is 27.610151\n",
+            "Loss after epoch 3990 is 27.602568\n",
+            "Loss after epoch 4000 is 27.595028\n",
+            "Loss after epoch 4010 is 27.587463\n",
+            "Loss after epoch 4020 is 27.57989\n",
+            "Loss after epoch 4030 is 27.572363\n",
+            "Loss after epoch 4040 is 27.564789\n",
+            "Loss after epoch 4050 is 27.557247\n",
+            "Loss after epoch 4060 is 27.54967\n",
+            "Loss after epoch 4070 is 27.542162\n",
+            "Loss after epoch 4080 is 27.5346\n",
+            "Loss after epoch 4090 is 27.527056\n",
+            "Loss after epoch 4100 is 27.519497\n",
+            "Loss after epoch 4110 is 27.511995\n",
+            "Loss after epoch 4120 is 27.504442\n",
+            "Loss after epoch 4130 is 27.496906\n",
+            "Loss after epoch 4140 is 27.489365\n",
+            "Loss after epoch 4150 is 27.481867\n",
+            "Loss after epoch 4160 is 27.474321\n",
+            "Loss after epoch 4170 is 27.466795\n",
+            "Loss after epoch 4180 is 27.459274\n",
+            "Loss after epoch 4190 is 27.451736\n",
+            "Loss after epoch 4200 is 27.444248\n",
+            "Loss after epoch 4210 is 27.436731\n",
+            "Loss after epoch 4220 is 27.429192\n",
+            "Loss after epoch 4230 is 27.42169\n",
+            "Loss after epoch 4240 is 27.414175\n",
+            "Loss after epoch 4250 is 27.406654\n",
+            "Loss after epoch 4260 is 27.399178\n",
+            "Loss after epoch 4270 is 27.391672\n",
+            "Loss after epoch 4280 is 27.384157\n",
+            "Loss after epoch 4290 is 27.376652\n",
+            "Loss after epoch 4300 is 27.36916\n",
+            "Loss after epoch 4310 is 27.361658\n",
+            "Loss after epoch 4320 is 27.35415\n",
+            "Loss after epoch 4330 is 27.346653\n",
+            "Loss after epoch 4340 is 27.339197\n",
+            "Loss after epoch 4350 is 27.331717\n",
+            "Loss after epoch 4360 is 27.324223\n",
+            "Loss after epoch 4370 is 27.316732\n",
+            "Loss after epoch 4380 is 27.30925\n",
+            "Loss after epoch 4390 is 27.30176\n",
+            "Loss after epoch 4400 is 27.29429\n",
+            "Loss after epoch 4410 is 27.286818\n",
+            "Loss after epoch 4420 is 27.279339\n",
+            "Loss after epoch 4430 is 27.271873\n",
+            "Loss after epoch 4440 is 27.264408\n",
+            "Loss after epoch 4450 is 27.256924\n",
+            "Loss after epoch 4460 is 27.249464\n",
+            "Loss after epoch 4470 is 27.241997\n",
+            "Loss after epoch 4480 is 27.23454\n",
+            "Loss after epoch 4490 is 27.227062\n",
+            "Loss after epoch 4500 is 27.219618\n",
+            "Loss after epoch 4510 is 27.212166\n",
+            "Loss after epoch 4520 is 27.20472\n",
+            "Loss after epoch 4530 is 27.197264\n",
+            "Loss after epoch 4540 is 27.189817\n",
+            "Loss after epoch 4550 is 27.182383\n",
+            "Loss after epoch 4560 is 27.174936\n",
+            "Loss after epoch 4570 is 27.167494\n",
+            "Loss after epoch 4580 is 27.160057\n",
+            "Loss after epoch 4590 is 27.152634\n",
+            "Loss after epoch 4600 is 27.145197\n",
+            "Loss after epoch 4610 is 27.137768\n",
+            "Loss after epoch 4620 is 27.130346\n",
+            "Loss after epoch 4630 is 27.122913\n",
+            "Loss after epoch 4640 is 27.115482\n",
+            "Loss after epoch 4650 is 27.108057\n",
+            "Loss after epoch 4660 is 27.100643\n",
+            "Loss after epoch 4670 is 27.093235\n",
+            "Loss after epoch 4680 is 27.085817\n",
+            "Loss after epoch 4690 is 27.078407\n",
+            "Loss after epoch 4700 is 27.070951\n",
+            "Loss after epoch 4710 is 27.063547\n",
+            "Loss after epoch 4720 is 27.056152\n",
+            "Loss after epoch 4730 is 27.048752\n",
+            "Loss after epoch 4740 is 27.041338\n",
+            "Loss after epoch 4750 is 27.033941\n",
+            "Loss after epoch 4760 is 27.02655\n",
+            "Loss after epoch 4770 is 27.019157\n",
+            "Loss after epoch 4780 is 27.01172\n",
+            "Loss after epoch 4790 is 27.004335\n",
+            "Loss after epoch 4800 is 26.99695\n",
+            "Loss after epoch 4810 is 26.989561\n",
+            "Loss after epoch 4820 is 26.982182\n",
+            "Loss after epoch 4830 is 26.974794\n",
+            "Loss after epoch 4840 is 26.967384\n",
+            "Loss after epoch 4850 is 26.960009\n",
+            "Loss after epoch 4860 is 26.952652\n",
+            "Loss after epoch 4870 is 26.945257\n",
+            "Loss after epoch 4880 is 26.937908\n",
+            "Loss after epoch 4890 is 26.930498\n",
+            "Loss after epoch 4900 is 26.923128\n",
+            "Loss after epoch 4910 is 26.915781\n",
+            "Loss after epoch 4920 is 26.908417\n",
+            "Loss after epoch 4930 is 26.901064\n",
+            "Loss after epoch 4940 is 26.89367\n",
+            "Loss after epoch 4950 is 26.886322\n",
+            "Loss after epoch 4960 is 26.87897\n",
+            "Loss after epoch 4970 is 26.871628\n",
+            "Loss after epoch 4980 is 26.864235\n",
+            "Loss after epoch 4990 is 26.856901\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 28.474577\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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Zfk1bCCHyK5vdxuAfP+Trs+up7lmDZc1XU8qttNqxxD+lpuK8dhWGWdPR3byB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\nrkJggg==\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe5819edf28>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "7D-NZKmOtyN0",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 4581
+        },
+        "outputId": "8801b9c0-4bde-4681-9dd0-6475253b441a"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.00004,n_epochs=5000,interval=20)"
+      ],
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 20 is 30.763958\n",
+            "Loss after epoch 40 is 30.730152\n",
+            "Loss after epoch 60 is 30.696346\n",
+            "Loss after epoch 80 is 30.662601\n",
+            "Loss after epoch 100 is 30.628874\n",
+            "Loss after epoch 120 is 30.595198\n",
+            "Loss after epoch 140 is 30.561579\n",
+            "Loss after epoch 160 is 30.527996\n",
+            "Loss after epoch 180 is 30.494442\n",
+            "Loss after epoch 200 is 30.460936\n",
+            "Loss after epoch 220 is 30.427427\n",
+            "Loss after epoch 240 is 30.394009\n",
+            "Loss after epoch 260 is 30.360598\n",
+            "Loss after epoch 280 is 30.32721\n",
+            "Loss after epoch 300 is 30.293924\n",
+            "Loss after epoch 320 is 30.26064\n",
+            "Loss after epoch 340 is 30.22738\n",
+            "Loss after epoch 360 is 30.194172\n",
+            "Loss after epoch 380 is 30.160954\n",
+            "Loss after epoch 400 is 30.127836\n",
+            "Loss after epoch 420 is 30.094738\n",
+            "Loss after epoch 440 is 30.061653\n",
+            "Loss after epoch 460 is 30.028646\n",
+            "Loss after epoch 480 is 29.99566\n",
+            "Loss after epoch 500 is 29.962688\n",
+            "Loss after epoch 520 is 29.92977\n",
+            "Loss after epoch 540 is 29.896935\n",
+            "Loss after epoch 560 is 29.864058\n",
+            "Loss after epoch 580 is 29.831255\n",
+            "Loss after epoch 600 is 29.79851\n",
+            "Loss after epoch 620 is 29.76578\n",
+            "Loss after epoch 640 is 29.733072\n",
+            "Loss after epoch 660 is 29.70044\n",
+            "Loss after epoch 680 is 29.667816\n",
+            "Loss after epoch 700 is 29.635218\n",
+            "Loss after epoch 720 is 29.60272\n",
+            "Loss after epoch 740 is 29.570194\n",
+            "Loss after epoch 760 is 29.537724\n",
+            "Loss after epoch 780 is 29.505316\n",
+            "Loss after epoch 800 is 29.472881\n",
+            "Loss after epoch 820 is 29.440538\n",
+            "Loss after epoch 840 is 29.408218\n",
+            "Loss after epoch 860 is 29.375917\n",
+            "Loss after epoch 880 is 29.343689\n",
+            "Loss after epoch 900 is 29.31147\n",
+            "Loss after epoch 920 is 29.279291\n",
+            "Loss after epoch 940 is 29.24718\n",
+            "Loss after epoch 960 is 29.21508\n",
+            "Loss after epoch 980 is 29.183018\n",
+            "Loss after epoch 1000 is 29.150942\n",
+            "Loss after epoch 1020 is 29.118973\n",
+            "Loss after epoch 1040 is 29.08702\n",
+            "Loss after epoch 1060 is 29.055073\n",
+            "Loss after epoch 1080 is 29.023207\n",
+            "Loss after epoch 1100 is 28.991348\n",
+            "Loss after epoch 1120 is 28.959568\n",
+            "Loss after epoch 1140 is 28.927784\n",
+            "Loss after epoch 1160 is 28.896032\n",
+            "Loss after epoch 1180 is 28.864332\n",
+            "Loss after epoch 1200 is 28.832664\n",
+            "Loss after epoch 1220 is 28.801033\n",
+            "Loss after epoch 1240 is 28.769424\n",
+            "Loss after epoch 1260 is 28.737865\n",
+            "Loss after epoch 1280 is 28.70637\n",
+            "Loss after epoch 1300 is 28.674866\n",
+            "Loss after epoch 1320 is 28.643435\n",
+            "Loss after epoch 1340 is 28.612\n",
+            "Loss after epoch 1360 is 28.58062\n",
+            "Loss after epoch 1380 is 28.54927\n",
+            "Loss after epoch 1400 is 28.517962\n",
+            "Loss after epoch 1420 is 28.486681\n",
+            "Loss after epoch 1440 is 28.455452\n",
+            "Loss after epoch 1460 is 28.424263\n",
+            "Loss after epoch 1480 is 28.393068\n",
+            "Loss after epoch 1500 is 28.361958\n",
+            "Loss after epoch 1520 is 28.330847\n",
+            "Loss after epoch 1540 is 28.299759\n",
+            "Loss after epoch 1560 is 28.268768\n",
+            "Loss after epoch 1580 is 28.237766\n",
+            "Loss after epoch 1600 is 28.206806\n",
+            "Loss after epoch 1620 is 28.175879\n",
+            "Loss after epoch 1640 is 28.144999\n",
+            "Loss after epoch 1660 is 28.114168\n",
+            "Loss after epoch 1680 is 28.083319\n",
+            "Loss after epoch 1700 is 28.052555\n",
+            "Loss after epoch 1720 is 28.021784\n",
+            "Loss after epoch 1740 is 27.991098\n",
+            "Loss after epoch 1760 is 27.960411\n",
+            "Loss after epoch 1780 is 27.929762\n",
+            "Loss after epoch 1800 is 27.899183\n",
+            "Loss after epoch 1820 is 27.868622\n",
+            "Loss after epoch 1840 is 27.838078\n",
+            "Loss after epoch 1860 is 27.807535\n",
+            "Loss after epoch 1880 is 27.777088\n",
+            "Loss after epoch 1900 is 27.746655\n",
+            "Loss after epoch 1920 is 27.71623\n",
+            "Loss after epoch 1940 is 27.685883\n",
+            "Loss after epoch 1960 is 27.65554\n",
+            "Loss after epoch 1980 is 27.625278\n",
+            "Loss after epoch 2000 is 27.594995\n",
+            "Loss after epoch 2020 is 27.564777\n",
+            "Loss after epoch 2040 is 27.534582\n",
+            "Loss after epoch 2060 is 27.504425\n",
+            "Loss after epoch 2080 is 27.474295\n",
+            "Loss after epoch 2100 is 27.444223\n",
+            "Loss after epoch 2120 is 27.414139\n",
+            "Loss after epoch 2140 is 27.384125\n",
+            "Loss after epoch 2160 is 27.354122\n",
+            "Loss after epoch 2180 is 27.324188\n",
+            "Loss after epoch 2200 is 27.294262\n",
+            "Loss after epoch 2220 is 27.26437\n",
+            "Loss after epoch 2240 is 27.234514\n",
+            "Loss after epoch 2260 is 27.204739\n",
+            "Loss after epoch 2280 is 27.174906\n",
+            "Loss after epoch 2300 is 27.145164\n",
+            "Loss after epoch 2320 is 27.115463\n",
+            "Loss after epoch 2340 is 27.085777\n",
+            "Loss after epoch 2360 is 27.056116\n",
+            "Loss after epoch 2380 is 27.02651\n",
+            "Loss after epoch 2400 is 26.996914\n",
+            "Loss after epoch 2420 is 26.967403\n",
+            "Loss after epoch 2440 is 26.937862\n",
+            "Loss after epoch 2460 is 26.90838\n",
+            "Loss after epoch 2480 is 26.878937\n",
+            "Loss after epoch 2500 is 26.849518\n",
+            "Loss after epoch 2520 is 26.82014\n",
+            "Loss after epoch 2540 is 26.790817\n",
+            "Loss after epoch 2560 is 26.761461\n",
+            "Loss after epoch 2580 is 26.732199\n",
+            "Loss after epoch 2600 is 26.702934\n",
+            "Loss after epoch 2620 is 26.673733\n",
+            "Loss after epoch 2640 is 26.644554\n",
+            "Loss after epoch 2660 is 26.615387\n",
+            "Loss after epoch 2680 is 26.58627\n",
+            "Loss after epoch 2700 is 26.55722\n",
+            "Loss after epoch 2720 is 26.52817\n",
+            "Loss after epoch 2740 is 26.499113\n",
+            "Loss after epoch 2760 is 26.470154\n",
+            "Loss after epoch 2780 is 26.441206\n",
+            "Loss after epoch 2800 is 26.412268\n",
+            "Loss after epoch 2820 is 26.383396\n",
+            "Loss after epoch 2840 is 26.35453\n",
+            "Loss after epoch 2860 is 26.325731\n",
+            "Loss after epoch 2880 is 26.296942\n",
+            "Loss after epoch 2900 is 26.268185\n",
+            "Loss after epoch 2920 is 26.239464\n",
+            "Loss after epoch 2940 is 26.210772\n",
+            "Loss after epoch 2960 is 26.182123\n",
+            "Loss after epoch 2980 is 26.153488\n",
+            "Loss after epoch 3000 is 26.124922\n",
+            "Loss after epoch 3020 is 26.09633\n",
+            "Loss after epoch 3040 is 26.067818\n",
+            "Loss after epoch 3060 is 26.039322\n",
+            "Loss after epoch 3080 is 26.010883\n",
+            "Loss after epoch 3100 is 25.982435\n",
+            "Loss after epoch 3120 is 25.954039\n",
+            "Loss after epoch 3140 is 25.925669\n",
+            "Loss after epoch 3160 is 25.897337\n",
+            "Loss after epoch 3180 is 25.86904\n",
+            "Loss after epoch 3200 is 25.840767\n",
+            "Loss after epoch 3220 is 25.812555\n",
+            "Loss after epoch 3240 is 25.78431\n",
+            "Loss after epoch 3260 is 25.756155\n",
+            "Loss after epoch 3280 is 25.728003\n",
+            "Loss after epoch 3300 is 25.699917\n",
+            "Loss after epoch 3320 is 25.671824\n",
+            "Loss after epoch 3340 is 25.643778\n",
+            "Loss after epoch 3360 is 25.615751\n",
+            "Loss after epoch 3380 is 25.587778\n",
+            "Loss after epoch 3400 is 25.559824\n",
+            "Loss after epoch 3420 is 25.531914\n",
+            "Loss after epoch 3440 is 25.504032\n",
+            "Loss after epoch 3460 is 25.476204\n",
+            "Loss after epoch 3480 is 25.448357\n",
+            "Loss after epoch 3500 is 25.42058\n",
+            "Loss after epoch 3520 is 25.392803\n",
+            "Loss after epoch 3540 is 25.365053\n",
+            "Loss after epoch 3560 is 25.337395\n",
+            "Loss after epoch 3580 is 25.30972\n",
+            "Loss after epoch 3600 is 25.282082\n",
+            "Loss after epoch 3620 is 25.254475\n",
+            "Loss after epoch 3640 is 25.226908\n",
+            "Loss after epoch 3660 is 25.199387\n",
+            "Loss after epoch 3680 is 25.171843\n",
+            "Loss after epoch 3700 is 25.144377\n",
+            "Loss after epoch 3720 is 25.11692\n",
+            "Loss after epoch 3740 is 25.089516\n",
+            "Loss after epoch 3760 is 25.06212\n",
+            "Loss after epoch 3780 is 25.0348\n",
+            "Loss after epoch 3800 is 25.00746\n",
+            "Loss after epoch 3820 is 24.980162\n",
+            "Loss after epoch 3840 is 24.952904\n",
+            "Loss after epoch 3860 is 24.925682\n",
+            "Loss after epoch 3880 is 24.898493\n",
+            "Loss after epoch 3900 is 24.87129\n",
+            "Loss after epoch 3920 is 24.844173\n",
+            "Loss after epoch 3940 is 24.817078\n",
+            "Loss after epoch 3960 is 24.789974\n",
+            "Loss after epoch 3980 is 24.762962\n",
+            "Loss after epoch 4000 is 24.735933\n",
+            "Loss after epoch 4020 is 24.708952\n",
+            "Loss after epoch 4040 is 24.681982\n",
+            "Loss after epoch 4060 is 24.655058\n",
+            "Loss after epoch 4080 is 24.628166\n",
+            "Loss after epoch 4100 is 24.601313\n",
+            "Loss after epoch 4120 is 24.574492\n",
+            "Loss after epoch 4140 is 24.547695\n",
+            "Loss after epoch 4160 is 24.520947\n",
+            "Loss after epoch 4180 is 24.494186\n",
+            "Loss after epoch 4200 is 24.467497\n",
+            "Loss after epoch 4220 is 24.440802\n",
+            "Loss after epoch 4240 is 24.41415\n",
+            "Loss after epoch 4260 is 24.387518\n",
+            "Loss after epoch 4280 is 24.360968\n",
+            "Loss after epoch 4300 is 24.334408\n",
+            "Loss after epoch 4320 is 24.307882\n",
+            "Loss after epoch 4340 is 24.281351\n",
+            "Loss after epoch 4360 is 24.2549\n",
+            "Loss after epoch 4380 is 24.228458\n",
+            "Loss after epoch 4400 is 24.202036\n",
+            "Loss after epoch 4420 is 24.175676\n",
+            "Loss after epoch 4440 is 24.14931\n",
+            "Loss after epoch 4460 is 24.123016\n",
+            "Loss after epoch 4480 is 24.096733\n",
+            "Loss after epoch 4500 is 24.070469\n",
+            "Loss after epoch 4520 is 24.044226\n",
+            "Loss after epoch 4540 is 24.018032\n",
+            "Loss after epoch 4560 is 23.99186\n",
+            "Loss after epoch 4580 is 23.965744\n",
+            "Loss after epoch 4600 is 23.939625\n",
+            "Loss after epoch 4620 is 23.913567\n",
+            "Loss after epoch 4640 is 23.887495\n",
+            "Loss after epoch 4660 is 23.861488\n",
+            "Loss after epoch 4680 is 23.835493\n",
+            "Loss after epoch 4700 is 23.809504\n",
+            "Loss after epoch 4720 is 23.783611\n",
+            "Loss after epoch 4740 is 23.757692\n",
+            "Loss after epoch 4760 is 23.731823\n",
+            "Loss after epoch 4780 is 23.705976\n",
+            "Loss after epoch 4800 is 23.680159\n",
+            "Loss after epoch 4820 is 23.654394\n",
+            "Loss after epoch 4840 is 23.628603\n",
+            "Loss after epoch 4860 is 23.60289\n",
+            "Loss after epoch 4880 is 23.577219\n",
+            "Loss after epoch 4900 is 23.551535\n",
+            "Loss after epoch 4920 is 23.525867\n",
+            "Loss after epoch 4940 is 23.50028\n",
+            "Loss after epoch 4960 is 23.474695\n",
+            "Loss after epoch 4980 is 23.449144\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 24.655712\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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CCGdmtVsZ+H0/vkpcSxmPMsxp/REvBr6kdiznY7fj/uUqDJMn4HLuLHYfHzKj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\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e749f98>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "zRdIQ89Ot6mn",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 2481
+        },
+        "outputId": "52ff1c03-11bf-4963-92ea-ee71dbe4e9f1"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.00004,n_epochs=5000,interval=40)"
+      ],
+      "execution_count": 25,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 40 is 30.730152\n",
+            "Loss after epoch 80 is 30.662601\n",
+            "Loss after epoch 120 is 30.595198\n",
+            "Loss after epoch 160 is 30.527996\n",
+            "Loss after epoch 200 is 30.460936\n",
+            "Loss after epoch 240 is 30.394009\n",
+            "Loss after epoch 280 is 30.32721\n",
+            "Loss after epoch 320 is 30.26064\n",
+            "Loss after epoch 360 is 30.194172\n",
+            "Loss after epoch 400 is 30.127836\n",
+            "Loss after epoch 440 is 30.061653\n",
+            "Loss after epoch 480 is 29.99566\n",
+            "Loss after epoch 520 is 29.92977\n",
+            "Loss after epoch 560 is 29.864058\n",
+            "Loss after epoch 600 is 29.79851\n",
+            "Loss after epoch 640 is 29.733072\n",
+            "Loss after epoch 680 is 29.667816\n",
+            "Loss after epoch 720 is 29.60272\n",
+            "Loss after epoch 760 is 29.537724\n",
+            "Loss after epoch 800 is 29.472881\n",
+            "Loss after epoch 840 is 29.408218\n",
+            "Loss after epoch 880 is 29.343689\n",
+            "Loss after epoch 920 is 29.279291\n",
+            "Loss after epoch 960 is 29.21508\n",
+            "Loss after epoch 1000 is 29.150942\n",
+            "Loss after epoch 1040 is 29.08702\n",
+            "Loss after epoch 1080 is 29.023207\n",
+            "Loss after epoch 1120 is 28.959568\n",
+            "Loss after epoch 1160 is 28.896032\n",
+            "Loss after epoch 1200 is 28.832664\n",
+            "Loss after epoch 1240 is 28.769424\n",
+            "Loss after epoch 1280 is 28.70637\n",
+            "Loss after epoch 1320 is 28.643435\n",
+            "Loss after epoch 1360 is 28.58062\n",
+            "Loss after epoch 1400 is 28.517962\n",
+            "Loss after epoch 1440 is 28.455452\n",
+            "Loss after epoch 1480 is 28.393068\n",
+            "Loss after epoch 1520 is 28.330847\n",
+            "Loss after epoch 1560 is 28.268768\n",
+            "Loss after epoch 1600 is 28.206806\n",
+            "Loss after epoch 1640 is 28.144999\n",
+            "Loss after epoch 1680 is 28.083319\n",
+            "Loss after epoch 1720 is 28.021784\n",
+            "Loss after epoch 1760 is 27.960411\n",
+            "Loss after epoch 1800 is 27.899183\n",
+            "Loss after epoch 1840 is 27.838078\n",
+            "Loss after epoch 1880 is 27.777088\n",
+            "Loss after epoch 1920 is 27.71623\n",
+            "Loss after epoch 1960 is 27.65554\n",
+            "Loss after epoch 2000 is 27.594995\n",
+            "Loss after epoch 2040 is 27.534582\n",
+            "Loss after epoch 2080 is 27.474295\n",
+            "Loss after epoch 2120 is 27.414139\n",
+            "Loss after epoch 2160 is 27.354122\n",
+            "Loss after epoch 2200 is 27.294262\n",
+            "Loss after epoch 2240 is 27.234514\n",
+            "Loss after epoch 2280 is 27.174906\n",
+            "Loss after epoch 2320 is 27.115463\n",
+            "Loss after epoch 2360 is 27.056116\n",
+            "Loss after epoch 2400 is 26.996914\n",
+            "Loss after epoch 2440 is 26.937862\n",
+            "Loss after epoch 2480 is 26.878937\n",
+            "Loss after epoch 2520 is 26.82014\n",
+            "Loss after epoch 2560 is 26.761461\n",
+            "Loss after epoch 2600 is 26.702934\n",
+            "Loss after epoch 2640 is 26.644554\n",
+            "Loss after epoch 2680 is 26.58627\n",
+            "Loss after epoch 2720 is 26.52817\n",
+            "Loss after epoch 2760 is 26.470154\n",
+            "Loss after epoch 2800 is 26.412268\n",
+            "Loss after epoch 2840 is 26.35453\n",
+            "Loss after epoch 2880 is 26.296942\n",
+            "Loss after epoch 2920 is 26.239464\n",
+            "Loss after epoch 2960 is 26.182123\n",
+            "Loss after epoch 3000 is 26.124922\n",
+            "Loss after epoch 3040 is 26.067818\n",
+            "Loss after epoch 3080 is 26.010883\n",
+            "Loss after epoch 3120 is 25.954039\n",
+            "Loss after epoch 3160 is 25.897337\n",
+            "Loss after epoch 3200 is 25.840767\n",
+            "Loss after epoch 3240 is 25.78431\n",
+            "Loss after epoch 3280 is 25.728003\n",
+            "Loss after epoch 3320 is 25.671824\n",
+            "Loss after epoch 3360 is 25.615751\n",
+            "Loss after epoch 3400 is 25.559824\n",
+            "Loss after epoch 3440 is 25.504032\n",
+            "Loss after epoch 3480 is 25.448357\n",
+            "Loss after epoch 3520 is 25.392803\n",
+            "Loss after epoch 3560 is 25.337395\n",
+            "Loss after epoch 3600 is 25.282082\n",
+            "Loss after epoch 3640 is 25.226908\n",
+            "Loss after epoch 3680 is 25.171843\n",
+            "Loss after epoch 3720 is 25.11692\n",
+            "Loss after epoch 3760 is 25.06212\n",
+            "Loss after epoch 3800 is 25.00746\n",
+            "Loss after epoch 3840 is 24.952904\n",
+            "Loss after epoch 3880 is 24.898493\n",
+            "Loss after epoch 3920 is 24.844173\n",
+            "Loss after epoch 3960 is 24.789974\n",
+            "Loss after epoch 4000 is 24.735933\n",
+            "Loss after epoch 4040 is 24.681982\n",
+            "Loss after epoch 4080 is 24.628166\n",
+            "Loss after epoch 4120 is 24.574492\n",
+            "Loss after epoch 4160 is 24.520947\n",
+            "Loss after epoch 4200 is 24.467497\n",
+            "Loss after epoch 4240 is 24.41415\n",
+            "Loss after epoch 4280 is 24.360968\n",
+            "Loss after epoch 4320 is 24.307882\n",
+            "Loss after epoch 4360 is 24.2549\n",
+            "Loss after epoch 4400 is 24.202036\n",
+            "Loss after epoch 4440 is 24.14931\n",
+            "Loss after epoch 4480 is 24.096733\n",
+            "Loss after epoch 4520 is 24.044226\n",
+            "Loss after epoch 4560 is 23.99186\n",
+            "Loss after epoch 4600 is 23.939625\n",
+            "Loss after epoch 4640 is 23.887495\n",
+            "Loss after epoch 4680 is 23.835493\n",
+            "Loss after epoch 4720 is 23.783611\n",
+            "Loss after epoch 4760 is 23.731823\n",
+            "Loss after epoch 4800 is 23.680159\n",
+            "Loss after epoch 4840 is 23.628603\n",
+            "Loss after epoch 4880 is 23.577219\n",
+            "Loss after epoch 4920 is 23.525867\n",
+            "Loss after epoch 4960 is 23.474695\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 24.655712\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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CCGdmtVsZ+H0/vkpcSxmPMsxp/REvBr6kdiznY7fj/uUqDJMn4HLuLHYfHzKj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\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e44d7f0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "hegOKw92uH-z",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 2397
+        },
+        "outputId": "b6d501ca-5172-4c1f-f61b-e3f289d03a33"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000001,n_epochs=6000,interval=50)"
+      ],
+      "execution_count": 26,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 1295.9073\n",
+            "Loss after epoch 100 is 63.946465\n",
+            "Loss after epoch 150 is 31.660282\n",
+            "Loss after epoch 200 is 30.812088\n",
+            "Loss after epoch 250 is 30.787823\n",
+            "Loss after epoch 300 is 30.78515\n",
+            "Loss after epoch 350 is 30.782993\n",
+            "Loss after epoch 400 is 30.780874\n",
+            "Loss after epoch 450 is 30.778784\n",
+            "Loss after epoch 500 is 30.776644\n",
+            "Loss after epoch 550 is 30.774532\n",
+            "Loss after epoch 600 is 30.772398\n",
+            "Loss after epoch 650 is 30.770298\n",
+            "Loss after epoch 700 is 30.76819\n",
+            "Loss after epoch 750 is 30.766048\n",
+            "Loss after epoch 800 is 30.763962\n",
+            "Loss after epoch 850 is 30.761843\n",
+            "Loss after epoch 900 is 30.759705\n",
+            "Loss after epoch 950 is 30.757616\n",
+            "Loss after epoch 1000 is 30.755512\n",
+            "Loss after epoch 1050 is 30.753355\n",
+            "Loss after epoch 1100 is 30.751272\n",
+            "Loss after epoch 1150 is 30.749168\n",
+            "Loss after epoch 1200 is 30.747019\n",
+            "Loss after epoch 1250 is 30.744928\n",
+            "Loss after epoch 1300 is 30.742826\n",
+            "Loss after epoch 1350 is 30.74068\n",
+            "Loss after epoch 1400 is 30.73858\n",
+            "Loss after epoch 1450 is 30.736498\n",
+            "Loss after epoch 1500 is 30.734343\n",
+            "Loss after epoch 1550 is 30.73224\n",
+            "Loss after epoch 1600 is 30.730146\n",
+            "Loss after epoch 1650 is 30.72802\n",
+            "Loss after epoch 1700 is 30.725908\n",
+            "Loss after epoch 1750 is 30.723812\n",
+            "Loss after epoch 1800 is 30.72168\n",
+            "Loss after epoch 1850 is 30.719574\n",
+            "Loss after epoch 1900 is 30.71744\n",
+            "Loss after epoch 1950 is 30.715351\n",
+            "Loss after epoch 2000 is 30.71323\n",
+            "Loss after epoch 2050 is 30.7111\n",
+            "Loss after epoch 2100 is 30.709015\n",
+            "Loss after epoch 2150 is 30.706919\n",
+            "Loss after epoch 2200 is 30.704775\n",
+            "Loss after epoch 2250 is 30.702675\n",
+            "Loss after epoch 2300 is 30.700596\n",
+            "Loss after epoch 2350 is 30.698442\n",
+            "Loss after epoch 2400 is 30.696346\n",
+            "Loss after epoch 2450 is 30.694263\n",
+            "Loss after epoch 2500 is 30.692125\n",
+            "Loss after epoch 2550 is 30.69002\n",
+            "Loss after epoch 2600 is 30.68789\n",
+            "Loss after epoch 2650 is 30.68579\n",
+            "Loss after epoch 2700 is 30.683687\n",
+            "Loss after epoch 2750 is 30.681559\n",
+            "Loss after epoch 2800 is 30.679474\n",
+            "Loss after epoch 2850 is 30.677382\n",
+            "Loss after epoch 2900 is 30.675234\n",
+            "Loss after epoch 2950 is 30.673141\n",
+            "Loss after epoch 3000 is 30.671059\n",
+            "Loss after epoch 3050 is 30.668932\n",
+            "Loss after epoch 3100 is 30.666815\n",
+            "Loss after epoch 3150 is 30.66473\n",
+            "Loss after epoch 3200 is 30.66261\n",
+            "Loss after epoch 3250 is 30.660498\n",
+            "Loss after epoch 3300 is 30.658367\n",
+            "Loss after epoch 3350 is 30.656279\n",
+            "Loss after epoch 3400 is 30.65419\n",
+            "Loss after epoch 3450 is 30.652048\n",
+            "Loss after epoch 3500 is 30.649956\n",
+            "Loss after epoch 3550 is 30.647867\n",
+            "Loss after epoch 3600 is 30.64573\n",
+            "Loss after epoch 3650 is 30.643633\n",
+            "Loss after epoch 3700 is 30.641554\n",
+            "Loss after epoch 3750 is 30.639425\n",
+            "Loss after epoch 3800 is 30.637318\n",
+            "Loss after epoch 3850 is 30.635193\n",
+            "Loss after epoch 3900 is 30.633112\n",
+            "Loss after epoch 3950 is 30.63102\n",
+            "Loss after epoch 4000 is 30.62888\n",
+            "Loss after epoch 4050 is 30.626783\n",
+            "Loss after epoch 4100 is 30.624706\n",
+            "Loss after epoch 4150 is 30.622576\n",
+            "Loss after epoch 4200 is 30.620474\n",
+            "Loss after epoch 4250 is 30.618343\n",
+            "Loss after epoch 4300 is 30.616268\n",
+            "Loss after epoch 4350 is 30.614176\n",
+            "Loss after epoch 4400 is 30.612043\n",
+            "Loss after epoch 4450 is 30.60995\n",
+            "Loss after epoch 4500 is 30.607868\n",
+            "Loss after epoch 4550 is 30.605743\n",
+            "Loss after epoch 4600 is 30.603645\n",
+            "Loss after epoch 4650 is 30.601515\n",
+            "Loss after epoch 4700 is 30.59944\n",
+            "Loss after epoch 4750 is 30.59735\n",
+            "Loss after epoch 4800 is 30.5952\n",
+            "Loss after epoch 4850 is 30.593122\n",
+            "Loss after epoch 4900 is 30.591034\n",
+            "Loss after epoch 4950 is 30.588896\n",
+            "Loss after epoch 5000 is 30.58681\n",
+            "Loss after epoch 5050 is 30.584696\n",
+            "Loss after epoch 5100 is 30.582617\n",
+            "Loss after epoch 5150 is 30.580532\n",
+            "Loss after epoch 5200 is 30.578392\n",
+            "Loss after epoch 5250 is 30.576303\n",
+            "Loss after epoch 5300 is 30.574226\n",
+            "Loss after epoch 5350 is 30.572102\n",
+            "Loss after epoch 5400 is 30.570004\n",
+            "Loss after epoch 5450 is 30.567873\n",
+            "Loss after epoch 5500 is 30.565802\n",
+            "Loss after epoch 5550 is 30.563715\n",
+            "Loss after epoch 5600 is 30.56158\n",
+            "Loss after epoch 5650 is 30.559486\n",
+            "Loss after epoch 5700 is 30.55741\n",
+            "Loss after epoch 5750 is 30.55529\n",
+            "Loss after epoch 5800 is 30.55319\n",
+            "Loss after epoch 5850 is 30.551075\n",
+            "Loss after epoch 5900 is 30.548998\n",
+            "Loss after epoch 5950 is 30.546913\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 32.61106\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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ihSyEUM0V62W6ffsy289tpX2Vl4hrMRsPnZREjrDZ8F68AENMFLpzZ3EWLkzG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\niYiIFMBBJiIiUgAHmYiISAH/A4MsC/jmOd7UAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e30ed68>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "qqD8N9L_uOsp",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 2733
+        },
+        "outputId": "c10ec149-df40-41d4-c266-1f79fd98f514"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=7000,interval=50)"
+      ],
+      "execution_count": 27,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 23.58116\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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UnNdH4TY2HN2Z09hLlCQlJJzU9z8C1+L1lyaNktsLzCrI62sqheW6TUEn4/jo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\nCCFEkPh/moMdbPLXoGwAAAAASUVORK5CYII=\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e2860f0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "ujkwfu8suVcU",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 5421
+        },
+        "outputId": "2ae2f1f8-9373-4565-8c93-e5918b826d26"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=15000,interval=50)"
+      ],
+      "execution_count": 28,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 16.160955\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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MGIGtrS2XL1/m0KFDjB49mlGjRjFx4kS2bduGq6srPXr00PvBCCFEcUjJSOGz\nE36sPr8CM7UZMzzn8LHHSFk3vIDMDx+Q+dZ6otIVtMGsgOLuqUgfUT9kHItOxlA/imMcrz68wpAD\n/bkad4VajrUJ6rCaBhUb6vU9DI2+xjFX37r/oKy+dcWKeqjS8JV4T1sIIcqy8Lgw/vPdW8SkxDCk\nwYf4eX6Gpaml0mUZPOlbFx8JbSGEyMP1R9d4Z3dXYlJiWPD6lwx8ebDSJRk+6VsXOwltIYR4wq3H\nN3nnu65EJd1j9qvzJLALQPrWJUNCWwgh/uVe4l3e+a4rtxNvMbXFDD5sNELpkgzak33rlIGDy1Tf\nuqRJaAshxF+ik6PptbsbNxKuM66pL2OajFe6JIOlehiL1aL5WK5dldW3bu2V1beuV1/p0ko1CW0h\nhAAeamLptbsb4fFhDPcYzcRmU5UuyTBJ31pREtpCiDLvUWo87+7pyeWHFxncYBgzPGfL07nykP18\n6/CwrL71rM9JGSx965IkoS2EKNMS0x7T5/tenIs+y/t1BzD3tQUS2E/I1bceMJikidK3VoKEthCi\nzEpOT+b9fe9y5v5p3nH3ZuEbAbLK2b9I39rwSGgLIcokTYaGgft9OH73F7rW6MGSdl9joi7eRwEb\njb+eby19a8MjoS2EKHPStGkMPTiAkFs/0rFaZ4Lar8JULf8cQlbfmlnTsLlyRfrWBkh+SoUQZUpG\nZgYfHx7CgRs/8MaLbVj55nrMTSSQ/t23RvrWBktCWwhRZmgztYz+8WP2RAbTyvU11nf+BgtTC6XL\nUlRefWvzZYEkulRTujSRBwltIUSZkKnLZMJPY9kRto2mlZqz6a1tWJlZKV2Wcp6cb/1S9ay+dcfO\nODnbgTx1ziBJaAshSj2dTsfUX3zZdHk9DZ08+KbLDmzMn/74w9Iux3xrWzsSZ84lZciH0rc2AhLa\nQohSTafT8dmJ6aw+v4K65euzvev/sC/noHRZijAJu4r1jCmUO3JI5lsbKQltIUSptuD/PmfZ71/h\n7lCLb7t9R3mLCkqXVOJUcQ+xWjhP5luXAhLaQohSKzB0MV+c8aeqXTV2dNuNs5Wz0iWVrPR0LNav\nxnrB57n61jLf2jhJaAshSqXl55Yx5+RMXrRxY1f373nBxlXpkkqU9K1LJwltIUSps/7iGvx+nUwl\nKxd2dN+Nm20VpUsqMbn61v0/yOpbOzkpXZrQAwltIUSpsvXKZib8NJaKlhXZ2W0P1e1rKF1Sicjd\nt36DxM/moa3/stKlCT2S0BZClBrbLmxj7NEROJZz5Nuuu6lVvrbSJRW/J/rW2movkTjrc9I6vSV9\n61JIQlsIUSrsu/Y9gw/0w9oAGzAAAAAgAElEQVTMhu1dg6lfsfSfYebZtx48DMqVU7o0UUwktIUQ\nRu/InwcZenAAFqYWfPP2Tho5v6J0ScVK+tZll4S2EMKo/Xz7Jwbtfx8TlQnf+3xPfesmSpdUbFRx\nD7PWCV+zUvrWZZSEthDCaJ28d4J++94lU5fJxre24VXNi+jSuGa29K3FX9QF3VCj0dC+fXt27doF\nwIYNG6hfvz5JSUkAXLhwgX79+mX/8vT0JDQ0NMc++vXrxzvvvJO9zYULF/R4KEKIsiT0/hl8vu9F\nWmYaqzttpE2VdkqXVCzMfjyEY5tW2E7xBW0miTPn8vDn06R1flsCuwwq8Jl2UFAQ9vb2AAQHBxMb\nG4uz8z+rC7388sts3LgRgISEBIYPH46Hh0eu/cybN49atWoVtW4hRBl2PuYP3v2+J8kZSazosJaO\n1TorXZLemYSHYT19svStRQ4FCu3IyEgiIiLw8vICoH379tjY2LBnz548t1+9ejUDBgxArS7wibwQ\nQhTIlYeX8d7dnYTURyxtt5xuNf+jdEl6JX1rkZ8Cpaq/vz+TJk3K/tzGxuap22o0Gn755Rfatcv7\nUlVgYCB9+/Zl+vTpaDSa5yxXCFGWXYuPoNfubsRqYvnCK5Detd9TuiT9SU/HYtXXlG/hgdXKr8l0\nq8Kj9d/waMduCWyR7Zln2sHBwXh4eODm5lagHR4+fBgvL688z7L79+9P7dq1qVKlCjNmzGDz5s0M\nHjz4qftydLTC1NSkQO9bWE5OZfeZuvok41h0Mob5ux53nV7fd+NB8n2WdF7CyOYj89zOKMdx/34Y\nNw4uXwY7O1i0CJORI7FXcL61UY6jAdL3OD4ztENCQrh16xYhISFERUVhbm6Oi4sLrVq1ynP7o0eP\n0qdPnzxf69ChQ/bHbdu2Zd++ffm+d1xc8rPKKxInJ9vSeadpCZNxLDoZw/zdTbxDt+DO3E64zXTP\n2bz70oA8x8vYxvHJvrXm333rhDQgTZG6jG0cDVVhxzG/oH9maAcEBGR/vGTJEipXrvzUwIasu8jr\n1KmT6+s6nY5BgwYRGBiInZ0dp06dwt3d/VlvL4Qo4+4n3+ed3V25mXAD32ZTGPnKGKVLKrJcfevX\nXidx9ny5DC6eqVDztIOCgjh+/DjR0dEMHToUDw8PfH19gaw7x//d8z527Bi3b9/Gx8cHb29vBg4c\niKWlJZUqVWLUqFH6OQohRKkUmxJL793diIyPYPQr4xjfdKLSJRVNejoWG9ZkzbeOi5P51uK5qXQ6\nnU7pIp6muC/PyCUg/ZBxLDoZw9ziNXH03N2VCzF/MKzhx8x+dT6qZwSbIY+j2Y+HsZk+GdOwq2Ta\n2pE8zjfr+dYGuE64IY+jMVHk8rgQQpS0x2kJvPd9Ty7E/EH/eh8UKLANlUl4WNY64YcPynxrUWQS\n2kIIg5KUnoTP3t6EPviNd2v7sOCNxUYZ2Nl967WrUGVkSN9a6IWEthDCYKRkpND/hz6cuneCHjV7\nEtBmGWqVkS3SJH1rUYwktIUQBiFNm8bg/f34+XYInV/qwrJ2KzFRF+86Dfr2ZN86ccYcg+1bC+Mk\noS2EUFy6Np1hBwdx+OZB2lZpz4o312JmYqZ0WQUmfWtRUiS0hRCK0mZqGXlkGPuu76F15TdY22kz\n5UyM48xU+taipEloCyEUk6nL5JOQkfwvYifNXVqy4a2tWJpaKl3Ws2Vk/PN8a+lbixIkoS2EUIRO\np2PSsfFsvbKZV5wb802XHVibWStd1jOZ/XgYmxlTML16RfrWosRJaAshSpxOp2P68Smsu7ia+hUa\nsLXLLmzN7ZQuK1/StxaGQEJbCFHi5p2azfJzy6jtWIdvu32Ho0V5pUt6KlXcQ6y+8M9aJ1z61kJh\nEtpCiBK1+MwCAkIX8ZJ9dXZ0201Fy4pKl5S3jAws1q/BesFc6VsLgyGhLYQoVpoMDedjzhF6/wwn\n751g77XdVLGtyq5u31PJ2kXp8vIkfWthqCS0hRB6o9PpuPYogt/unyH0r18XYy+QnpmevU11+xps\n7bKLyrYvKlhp3nL1rfsNImnSNOlbC4MhoS2EKLSHmlhC75/JDumzD34jPjU++3UztRkNKjakcaWm\n2b9esqtucGuJ59m3/mwe2pcbKF2aEDlIaAshCiRVm8qFmD9yhPSNhOs5tqlqV422VdrT2LkpTVya\n8XLFhoa9UEpefeuZc0nr/Lb0rYVBktAWQuSi0+m4kXA9+xJ36IMznI/+g7TMtOxt7Ms54OXWlsaV\nmtLEuSmvVGpquDeV5UH61sIYSWgLIYjXxBH64LfskD774DdiNbHZr5uqTalfoQGNKzXJOouu1Izq\nDjWM7wlcSN9aGDcJbSHKmDRtGpdiL/xzs9iDM0TGR+TYxs22Cq9VfoMmLk1p7NyMBk4NjWN50Xyo\n4uOy1gmXvrUwYhLaQpRiOp2OW49v/tWH/j9+u3+G8zHnSNWmZm9ja25H6xe9aOL8z81izlbOClat\nZ9K3FqWIhLYQpUhC6iPOPgjNPoP+7f4ZYlKis183UZlQt0L9vy5xZwW0u2Mto7zMXRBmR49kPd/6\n6hUybWxJnD6blKEfSd9aGC0JbSGMlDZT+89l7gdZl7rD48LQocveprLNi3St0SM7pBs4NTKKh3IU\nlUlEeFbf+tABdCpVVt964lR0zqXoCoIokyS0hTAymgwN31zZxLKzX3Hz8Z/ZX7c2s6GV62s0qdQs\n647uSk0NdsWxYhMXh7XfNCxXr8jqW7/aOmudcOlbi1JCQlsII5GYnsj6C2sIOreEB8n3sTCx4N3a\nPrR4wZPGlZpS27EOJmoTpctUxl99axZ+jtXDh9K3FqWWhLYQBi5eE8eq88tZ+UcQcalxWJvZMPKV\nsXzYaASVrCopXZ7i/t23xlb61qJ0k9AWwkA9SH7A8nPLWHthFYnpj3Eo58CEZpMZ0uBDg36UZUnJ\nq29tuXAeKWorpUsTothIaAthYG4/vsWy379i86UNaLQanCydGdfUl4H1P8DG3Fbp8hSnio/LWic8\nj761pZMtRD9WukQhik2BQluj0dClSxeGDx9Oz5492bBhA/7+/pw+fRpr66w7UevXr0/jxo2zv2fd\nunWYmPzTX7t37x6+vr5otVqcnJxYuHAh5ubmej4cIYzXtfgIAkO/5NuwraRnpvOijRsjG4+lT533\njX5hE714cr511WpZfeu3ukjfWpQZBQrtoKAg7O3tAQgODiY2NhbnJ6ZO2NjYsHHjxqfuIzAwEB8f\nHzp37szixYvZsWMHPj4+RShdiNLhUuxFvj72FdsvbidTl0kNh5qMaTyed9y9MTMxU7o8gyDzrYXI\n8szQjoyMJCIiAi8vLwDat2+PjY0Ne/bsea43OnXqFLNmzQKgTZs2rFmzRkJblGmh988Q8Nsi9t/Y\nB0D9Cg0Y22Q8Xap3L7t3gT8hd996IEkTp8l8a1FmPTO0/f398fPzIzg4GMg6o85LWloa48eP586d\nO3Ts2JFBgwbleD0lJSX7cniFChWIjo7OazdClGo6nY7jd3/hy98Wcez2UQCaVGrGzLbTae7wusE9\nZ1opefatP5uHtkFDpUsTQlH5hnZwcDAeHh64ubk9c0e+vr5069YNlUrF+++/T9OmTWnQIO8FDXQ6\nXZ5ff5KjoxWmpsV7xuHkJDf26IOMY/50Oh0/RPzA3J/ncvzWcQDavdSOqa2n4lXNS8L6bxkZsGIF\nTJ8OsbFQvTosWoR5jx6UL+AYyc+ifsg46oe+xzHf0A4JCeHWrVuEhIQQFRWFubk5Li4utGrVKte2\nffr0yf64ZcuWhIWF5QhtKysrNBoNFhYW3L9/P1dPPC9xccnPcyzPzcnJlmi507TIZByfTpupZe+1\n3QSEfsGFmD8A6FitM2Maj6epS3MAYmISZQzJ3bdO/nffOiaxQPuQcdQPGUf9KOw45hf0+YZ2QEBA\n9sdLliyhcuXKeQb2tWvXWLZsGYsWLUKr1RIaGkqnTp1ybNOqVSsOHDhA9+7dOXjwIK1bt37e4xDC\naKRr09kZvp3A0MVExIejQkWPmj0Z0/hT6ld8WenyDIpJRDjWM6dS7uB+6VsL8QzPPU87KCiI48eP\nEx0dzdChQ/Hw8MDX1xcXFxd69eqFWq2mbdu2NGzYkMuXL3Po0CFGjx7NqFGjmDhxItu2bcPV1ZUe\nPXoUx/EIoagn1wU3VZvSp877jG78CTUc3JUuz6Dk6lu3ei1rvrX0rYV4KpWuoA1mBRT35Rm5BKQf\nMo5Z64JvuLiWoN+XcD85CgsTC/rW688IjzG8aPvse0LK1BhmZGCxYW3WfOuHD/U637pMjWMxknHU\njxK/PC6EyJ+sC/58zI4ewWbGFEyvXM6ab+33GSnDPpb51kIUkIS2EIUg64I/n1x96/cHkDTJT/rW\nQjwnCW0hnsOdx7dZ9vtXbLq0XtYFLwDpWwuhXxLaQhTAtUeRLAn9ku1Xv5F1wQuiGPvWQpRlEtpC\n5ONS7EW++m0R30X+T9YFLyCzkB+z5ltL31oIvZPQFiIPsi7485O+tRDFT0JbiL88bV3wT5p8Soeq\nnWSp0afI6lsvwHL1culbC1HMJLSFAE7ePc7skzP4v6hTALR+0YtPmnzKq66tJayf5sm+dZVqJM6c\nQ9rbXaVvLUQxkdAWZd6peyfpvac7qdrUXOuCi7zl6ltPm5XVt7awULo0IUo1CW1Rpl17FMmAH94j\nIzODLW9/S/uqHZUuyaDl2beeOA1dJVlIRoiSIKEtyqyHmlh8vu/FQ81DvvAKlMDOh/SthTAMEtqi\nTErVpjLwh75cexTJqFc+oV+9gUqXZJgyMrDYuA5r/znStxbCAEhoizJHp9Mx5sfhnLx3nO41ejK1\n5QylSzJI0rcWwvBIaIsyx///5rIr/FuaVmpOYLsg1Cq10iUZFJPIcKxnTqPcgR+kby2EgZHQFmXK\n1iubWXxmAVXtqrHhra2yBOm/qB7FY7XIX/rWQhgwCW1RZvx8+yfGhYzCoZwD37y9k4qWFZUuyTBI\n31oIoyGhLcqEqw+vMGj/+6hQsa7TFmo6uitdkkHI0be2tpG+tRAGTkJblHoPkh/Qd29vEtIesazd\nClpVfk3pkhSXq2/dt3/WOuHStxbCoEloi1ItOT2Z/vve5ebjP5nQbDK9a7+ndEmKUj2K/2e+dXo6\naZ6vkjRnPhkNGildmhCiACS0RamVqctkxJFhhD74De/affi06SSlS1LO333rBXNRx8Zm9a1nzCat\nSzfpWwthRCS0Rak167gfe6/t5lXX1iz2WlJmH/xh9tPRrL715UvStxbCyEloi1Jp7YVVBJ1bQk0H\nd9Z22oS5ibnSJZU4k2sRWM+YKn1rIUoRCW1R6hz58yCTf/6UipYV2fL2DhwsHJUuqURJ31qI0ktC\nW5QqF2LOM+TgQMzV5mzovJVq9i8pXVLJkb61EKWehLYoNe4l3qXv3t4kpSeyuuOGMvVMbOlbC1E2\nSGiLUiEx7TF993lzL+ku0z1n07VGD6VLKhEm1yKy5lvv3yd9ayHKgAI9KUGj0dC+fXt27doFwIYN\nG6hfvz5JSUnZ2+zbt49evXrh7e3Nl19+mWsfkyZNomvXrvTr149+/foREhKinyMQZV5GZgbDDg7i\nQswf9Ks3iBEeo5UuqdipHsVjPX0Kjq1bUG7/PtI8XyX+8DESv1wqgS1EKVagM+2goCDs7e0BCA4O\nJjY2Fmdn5+zXU1JSWLRoEbt378ba2hpvb2+6du1KzZo1c+xn3LhxtGnTRo/li7JOp9Mx9RdfDt88\nSBu3dvi//kXpntqVkYHFpvVZ64THxqKtUpXEGXOkby1EGfHM0I6MjCQiIgIvLy8A2rdvj42NDXv2\n7MnextLSkt27d2NjYwOAg4MD8fHxxVOxEP+y/I9lrL2wirrl67Oq43pM1aW342N2LAQbv0n/6lvP\nJGXYcOlbC1GGPPPyuL+/P5Mm/bOS1N/B/KS/v3716lXu3LlDo0a5p5ds2rSJ/v3788knn/Dw4cPC\n1iwEAHuv7WHGr1OpZOXClre/xdbcTumSioXJtQjs+r+HQ69umFy5TErf/jw8eZaU0eMksIUoY/I9\nLQkODsbDwwM3N7cC7ezGjRt8+umnfPHFF5iZmeV4rXv37jg4OFC3bl1WrFjB0qVLmT59er77c3S0\nwtTUpEDvXVhOTrbFuv+yoqTH8fSd0ww/PAQrMyv2vb8Xjxfqluj7F4dcYxgfD7Nnw5IlkJ4Or7+O\n6ssvsWzcGHkK+NPJ32n9kHHUD32PY76hHRISwq1btwgJCSEqKgpzc3NcXFxo1apVrm2joqIYMWIE\nCxYsoG7d3P+Aenp6Zn/ctm1bZs6c+czi4uKSC3AIhefkZEt09ONifY+yoKTH8WbCn7y9swup2lQ2\ndP4GN1N3o/9zzDGGz+pbG/mxFif5O60fMo76UdhxzC/o8w3tgICA7I+XLFlC5cqV8wxsgKlTpzJz\n5kzq16+f5+ujRo3C19cXNzc3Tp06hbu7PM9YPL9HqfH03dubmJRo5rVeyJvVOitdkl5J31oIkZ/n\nvmsnKCiI48ePEx0dzdChQ/Hw8KB3796cOXOGwMDA7O0GDhyIq6srhw4dYvTo0fTt25exY8diaWmJ\nlZUV8+bN0+uBiNIvTZvGBwf6czXuCh82HM7gBh8qXZL+hIdjN3qszLcWQuRLpdPpdEoX8TTFfXlG\nLgHpR0mMo06nY+zREXxzZROdXnqbtR03YaIu3vsdSsLf64RbrV4Of68TPnseGQ09lC7NKMnfaf2Q\ncdSPEr88LoShCPhtEd9c2YSH0ysEtV9l/IGdkYHF5g1Yz5+NOjYWqlXjkZ+sEy6EyF+BVkQTQkm7\nwr9l3unZvGjjxsa3t2NtZq10SUVidiwEx3atsZ0wFjSpJE6bCZcvk9a1uwS2ECJfcqYtDNrJeycY\nfeRjbM3t2Pz2t1SyMt4eb651wn36kTzZj8xKLthYWMDjdKVLFEIYOAltYbCuxUcwYN97ZJLJ6o4b\nqFuhntIlFYrqUTxWixdiuerrrOdbt2yV9Xxr6VsLIZ6ThLYwSLEpsfTZ24u41Di+9FqKl1tbpUt6\nfk/0rbPmW88mrYtcBhdCFI6EtjA4mgwNA37ow/VH1xjTeDx96/VXuqTnljXfejKmly/KfGshhN5I\naAuDkqnLZOzR4ZyOOkmPmj2Z3MJP6ZKeS359ayGEKCoJbWFQ/E/PYVf4Dpq5tCCw7deoVcYxwUH6\n1kKIkiChLQzGlssb+fK3RVSze4kNnbdiYWoEl5Klby2EKEES2sIgHLsdwqc/jcGhnAPfdNlBBcsK\nSpf0TLn61lNnkPLhCOlbCyGKjYS2UNzVh1f4YH8/1KhZ3/kbajgY9sNksvrWfpTbv1f61kKIEiWh\nLRR1P/k+Pnt7kZD2iP+2X4mn66tKl/RUqoRHWX3rlUH/9K1nzyOj0StKlyaEKCMktIViktOT6b/v\nXW49vsnE5lPpVetdpUvKm1b7z/OtY2Kkby2EUIyEtlCENlPL8MNDOfsglHdr+zCuia/SJeXJ7Oef\nsJk2SfrWQgiDIKEtFDHrhB/7ru/htcqv84VXICoDO2PN1bfu8z7JU6ZL31oIoSgJbVHi1lxYydfn\nluLuUIs1HTdibmKudEnZnuxbp7fwJHHOfOlbCyEMgoS2KFGHbuxnys8TqGjpxJYuO3CwcFS6pCxP\n9q3dqmT1rbv2kL61EMJgSGiLEnM+5g+GHhyEudqcjW9tpapdNaVLAv7qW/tNxvTSBXRW1tK3FkIY\nLAltUSLuJt6h797epGQks6rjBppUaqZ0SaivRWIzc1p231rzXl+Sps6QvrUQwmBJaItil5j2mL57\nvYlKuscMzzl0rdFd0Xqkby2EMFYS2qJYZWRmMOTgAC7GnmdA/cEM9xilXDFa7T/rhEvfWghhhCS0\nRbHR6XRM/nkCP948TNsq7ZnXeqFiU7ukby2EKA0ktEWxCTq3lPUXV1OvwsusfHMdpuqS/3FTX4vE\nZpYf5X74XuZbCyGMnoS2KBZ7Ir9j1vFpuFi/wJa3v8XW3K5E31/61kKI0khCW+iVTqfjVNRJRhwe\niqWpFZvf2o6rTeWSK0D61kKIUkxCWxRKujadPxNuEB4fxr2rf/L7nfOEx4URER/Oo9R41Co1Gztv\npYFToxKr6cm+ddKU6SR/OAIsLUusBiGEKE4FCm2NRkOXLl0YPnw4PXv2ZMOGDfj7+3P69Gmsra0B\n2L17N+vXr0etVuPt7U3v3r1z7OPevXv4+vqi1WpxcnJi4cKFmJsbzvKVIm8JqY8Ijw/LCuS4cMLj\nw4iIC+N6wjUyMjNybGuqNuUlu+q0cn0N79p96FCtU4nU+O++NSDzrYUQpVaBQjsoKAh7e3sAgoOD\niY2NxdnZOfv15ORkli1bxo4dOzAzM6NXr1506NABBweH7G0CAwPx8fGhc+fOLF68mB07duDj46Pn\nwxGFkanL5G7inb/OlLMCOjwujPD4MB4k38+1vZ25PY2cXsHdsRY1HWrRtGojnNVuVLWrhpmJWYnV\nrUp4hNWXi7Bc8V/pWwshyoRnhnZkZCQRERF4eXkB0L59e2xsbNizZ0/2NufOnaNBgwbY2toC0Lhx\nY0JDQ2nbtm32NqdOnWLWrFkAtGnThjVr1khol7CUjBSuxUdmB3PW7+FExoeTnJGcY1sVKtxsq9C2\nSnvcHWpR07FW9u9Olk45pm45OdkSHf245A5E+tZCiDLqmaHt7++Pn58fwcHBANjY2OTaJiYmhvLl\ny2d/Xr58eaKjo3Nsk5KSkn05vEKFCrleF/qh0+mISYn554z5r8vZ4fHh3Er4Ex26HNtbmlpSw8Ed\ndwf3HMFc3b4GVmZWCh3F05n9cizr+dbStxZClEH5hnZwcDAeHh64ubk91051Ol2RXv+bo6MVpqYm\nz/Xez8vJybZY919cMjIzuBZ3jSsxV3L9itPE5drexcaFN6q9QZ0KdahT8Z9fbvZuqFXqItdT7OMY\nEQETJsBf/3lk4EBUn3+O9QsvYF2871xijPVn0dDIOOqHjKN+6Hsc8w3tkJAQbt26RUhICFFRUZib\nm+Pi4kKrVq1ybOfs7ExMTEz25w8ePMDDwyPHNlZWVmg0GiwsLLh//36OnvjTxMUlP3Oboijxy7qF\nkJSexNWHl7PvzP77svb1R9dIz0zPse3fN4K1fOHVv86Y3f/qO7tjX84h987TITYmqcg1Fuc4PrNv\nbeB/fgVlDD+LxkDGUT9kHPWjsOOYX9DnG9oBAQHZHy9ZsoTKlSvnCmyARo0aMW3aNBISEjAxMSE0\nNJQpU6bk2KZVq1YcOHCA7t27c/DgQVq3bv28x1Hm7In8jk+OjiQh7VGOr9uZ29PQqRHujrWp6VAL\n978ua5f0jWDFSvrWQgiRy3PP0w4KCuL48eNER0czdOhQPDw88PX1Zfz48QwePBiVSsWIESOwtbXl\n8uXLHDp0iNGjRzNq1CgmTpzItm3bcHV1pUePHsVxPKWCJkPDzONTWXNhJVamVgxuMIzajnWzzpod\na+Fs6azYGt4lQfrWQgiRN5WuoA1mBRT35RlDvAR07VEkQw8M5HzMOeqUr8vKN9dTu3wdpcvKl77G\nUX39WtZ8631ZMxPK0nxrQ/xZNEYyjvoh46gfJX55XJSs4PCdjAsZTWL6Y3zq9OPz1gsN8g5ufVM9\nTvhnnfC0NNKbt8zqW3s0Vro0IYQwKBLaBiAlIwW/Xyaz4dIarEytWdZuBb1rv6d0WcVPq8Viy0as\n581GHRON1q0KSdM/I7Xbf6RvLYQQeZDQVlhEXDhDDg7gUuwF6pavz6qO63F3rKV0WcUuV996sh/J\nH42UvrUQQuRDQltBO8O28+lPY0lKT6RfvUHMeW0+lqalO7Ty7FtPmU6mywsKVyaEEIZPQlsBKRkp\nTP3Zl02X12NtZsPyDmv4j3svpcsqVtK3FkKIopPQLmHhcWEMOdCfyw8v8XLFhqx6cx3VHWoqXVbx\nkb61EELojYR2Cdp2ZQsTj40jOSOZQS8PYVarz7EwtVC6rGJj9uvPWX3ri+elby2EEHogoV0CktKT\nmPLzBL65sglbcztWvbmebjX/o3RZxUb61kIIUTwktIvZlYeXGXpgAFfjrtDI6RVWvLmWl+yrK11W\nsVA9TvhnnXDpWwshhN5JaBcTnU7H1iubmfTzeFIyUhjS4ENmtJpDOZNySpemf1otFhvX/dO3ftEt\nq2/dvaf0rYUQQo8ktItBYnoiE38ax7dhW7Ezt2dZx5V0qdFN6bKKhdmvP8PMKdieOyd9ayGEKGYS\n2np2KfYiQw8MIDw+jFecG7PizXVUtaumdFl6l6tv/a5P1jrh0rcWQohiI6GtJzqdjk2X1zP1Z180\nWg0fNhqBX8tZmJuYK12aXuXVtzZbtoTHVWsrXZoQQpR6Etp6kJj2mE9/GsOu8B04lHNgxZvr6PTS\nW0qXpV9aLRbfbML6889y9a2dnO1AnggkhBDFTkK7iM7H/MHQAwO49iiSJpWaseLNtbjZVlG6LL0y\n+/VnrP0mY3bhD+lbCyGEgiS0C0mn07Hu4mqm/zqZVG0qIzzGMKXFdMxMzJQuTW/UN65n9a337gak\nby2EEEqT0C6EhNRHjA8Zw3eRuyhvUZ41HTfSoVonpcvSG5lvLYQQhklC+zmde3CWoQcHciPhOs1d\nWrLizbW42lRWuiz9yKdvLfOthRBCeRLaBaTT6VhzYQUzfp1KWmYaYxqPZ2LzqZiqS8cQ5uxbW5E0\naRrJH4+SvrUQQhiQ0pE4xexRajxjj45k77XdVLCowLL2K2lbpb3SZemF9K2FEMJ4SGg/w9n7vzH0\n0CBuJtzA0/VVvm6/mhdsXJUuq8hy9a2btcjqW7/SROnShBBCPIWE9lPodDpW/PFfPjsxnYzMDMY1\nmcCnzSYb/+VwrRaLrZuz+tbRD6RvLYQQRsTIE6h4xGkeMuboCPZf30tFSyeC2q/iDbc2SpdVZGbH\nf8F62iTpWwshhJGS0O1s1fkAAA38SURBVH7CmajTDDs4iNuJt3it8usEtV9FJWsXpcsqEulbCyFE\n6SCh/ZdMXSZBvy9l7qmZaDO1TGg2mXFNfDFRmyhdWqGpHidgFfAFlsuXSd9aCCFKAQlt4KEmllFH\nPuLQnwdwtqrE1x1W81rl15Uuq/Ce7FtXfjGrb93jHelbCyGEESvzoX3q3kk+PDiIu0l3eOPFNixr\nvxJnK2elyyo06VsLIUTpVeDQ1mg0dOnSheHDh+Pp6Ymvry9arRYnJycWLlxIWFgY/v7+2dtHRESw\nbNkyGjf+Z+nLfv36kZycjJWVFQATJ07k5Zdf1uPhFFymLpP5v8xn2o/T0KFjcnM/xjQZj1qlVqSe\nosrVt/buk9W3fsH4p6cJIYTIUuDQDgoKwt7eHoDAwEB8fHzo3LkzixcvZseOHfj4+LBx40YAEhIS\nGD58OB4eHrn2M2/ePGrVqqWn8gsnJiWGkUeG8ePNw7hYv8DyDmvwdH1V0ZoKS/rWQghRdhTotDIy\nMpKIiAi8vLwAOHXqFO3atQOgTZs2nDhxIsf2q1evZsCAAajVhnfWeuLur7Td/io/3jxMp5qd+NH7\nV+MMbK0Wi80bKN+yMVZLviTTyZmE5WuI//6gBLYQQpRSBTrT9vf3x8/Pj+DgYABSUlIwNzcHoEKF\nCkRHR2dvq9Fo+OWXXxgzZkye+woMDCQuLo4aNWowZcoULCwsnvq+jo5WmJrq7+7tBb8uYPKRyahQ\nMb/dfCa8OsE4L4f/9BN88gmcPQtWVjB7Nibjx2OnYN/ayclWsfcuLWQM9UPGUT9kHPVD3+P4zNAO\nDg7Gw8MDNze3PF/X6XQ5Pj98+DBeXl55nmX379+f2rVrU6VKFWbMmMHmzZsZPHjwU987Li75WeUV\nWGJ6IpMOT+IFa1eWv7mWFi+0RK1SEx39WG/vUdzUN65j89l0yn3/HfBE3zoxAxKVORYnJ1ujGkdD\nJGOoHzKO+iHjqB+FHcf8gv6ZoR0SEsKtW7cICQkhKioKc3NzrKys0Gg0WFhYcP/+fZyd/7nb+ujR\no/Tp0yfPfXXo0CH747Zt27Jv377nOY4isTGz4ei7x3nR5kXsytmX2Pvqg+pxAlZfLcby66VZfeum\nzbP61o2bKl2aEEKIEvTM0A4ICMj+eMmSJVSuXJmzZ89y4MABunfvzsGDB2ndunX2NhcuXKBOnTq5\n9qPT6Rg0aBCBgYHY2dlx6tQp3N3d9XQYBVOvQv0Sfb8ik/nWQggh/qVQ87RHjRrFxIkT2bZtG66u\nrvTo0SP7tYSEBGxsbLI/P3bsGLdv38bHxwdvb28GDhyIpaUllSpVYtSoUUU/glLK7PgvWc+3Pn8u\na771/7d377ExNWgYwJ+Z0q9T5nNLG3xEIhHENUWipBgV1xLL9JpGUCVa9lO1Lb6V1d2I2wbpH4s0\nkQrxWSHbdJNm6UaasIq4rHVtXUqlVNttaZle1um7fwzj1supns45p31+iQQ9Z/p6Qh9n3pnT1F/c\n77f+8HY5IiLqeizy9VLaQDp6p2LEvY312VP3+62b2lsblBFzNBtmqA3mqA3mqA1ddtrkHZa3Ne73\nW3NvTUREzWBp601R4PfXE+ixI417ayIiahFLW0fd8//lvk8499ZERKQCS1sH1mdP3e+3/rv7ZjV1\n4VHuvfXAn3SejIiIjIyl7UXcWxMRUXuwtL2hqb31tjTU/8bJvTUREanG0u5g3FsTEZFWWNodhHtr\nIiLSGktbY5a3NZ/uE15fz701ERFphqWtlcZG933CubcmIqIOwtLWwDd765StcCX8lntrIiLSFEu7\nHb7ZWzsj8e7327m3JiKiDsHS/g7f7K0nTHLvrSdM0ns0IiLqxFjabfH13nrgT+77hHNvTUREXsDS\nVqn75Uvo8Usq99ZERKQblnYrrM+eosef/gC/7L8B4N6aiIj0w9JuBvfWRERkNCztrzU24ocP9wn3\nKXvl3ltvS0P9knDurYmISFcs7c90v3zJ/X7r//wbYrPh3e+2wJX4M/fWRERkCCxtcG9NRETm0LVL\nu6YGPXakcW9NRESm0DVL+8PeGjv/CP/SUu6tiYjIFLpcaX++twb31kREZCJdp7QVBfafE+B36lcA\n7r213/4/w/VDL50HIyIiUseq9wBeU1cH39x/4H8TJqEq55+o+UsGMGiQ3lMRERGp1nWutHv0wH/v\nPga6dZ0/MhERdS6qGqyurg5hYWFISEhAcHAwUlJSoCgKAgICsHfvXvj6+mLUqFEICgrynJOZmQkf\nHx/Pr1++fNnkeV7FwiYiIhNT9fT4wYMH0auXe/ebnp6OmJgYnDhxAkOGDMHp06cBAD179sSxY8c8\nPz4v7JbOIyIiInVaLe3Hjx/j0aNHmDFjBgDgypUrCA0NBQA4HA7k5+er+kTfex4RERG5tfp88e7d\nu7Ft2zZkZWUBAGpraz1Pa/fr1w/l5eUAgIaGBiQnJ6OkpARz5szBihUrvnic5s5rSZ8+/ujWzafV\n49ojIMDeoY/fVTDH9mOG2mCO2mCO2tA6xxZLOysrC+PHj8fgwYOb/LiIeH6ekpKCRYsWwWKxIDY2\nFhMnTsSYMWNaPa8lVVUuVcd9r4AAO8rLazr0c3QFzLH9mKE2mKM2mKM2vjfHloq+xdLOy8vD8+fP\nkZeXh9LSUvj6+sLf3x91dXXw8/PDq1evEBgYCACIjo72nDd58mQUFhZ+UdrNnUdERETqtLjTPnDg\nAM6cOYNTp04hPDwcCQkJmDJlCs6ePQsAOHfuHEJCQvDkyRMkJydDRPD+/XvcuHEDw4YN++KxmjqP\niIiI1GvzzVXWr1+PrKwsxMTE4PXr11i8eDGGDh2K/v37w+l0Ijo6GtOnT8fYsWNx//59pKenN3se\nERERqWcRtQtmHXT0ToV7G20wx/ZjhtpgjtpgjtroiJ1217mNKRERkcmxtImIiEyCpU1ERGQSht5p\nExER0Se80iYiIjIJljYREZFJsLSJiIhMgqVNRERkEixtIiIik2BpExERmUSr30/b7Pbs2YPr16/j\n/fv3WLNmDWbPng0AuHDhAlatWoWCggIAwIMHD7B161YAQGhoKBITE3Wb2YjU5rh//35cuXIFIoJZ\ns2YhPj5ez7EN5+scz58/j7t376J3794AgLi4OMyYMQPZ2dk4evQorFYrIiIiEB4ervPkxqE2w5yc\nHBw5cgRWqxXBwcFISkrSeXJjUZvjRxs3boSvry927dql08TGpDZHzTpGOrH8/HxZtWqViIhUVlbK\n9OnTRUSkrq5OYmNjZerUqZ5jnU6n3LlzRxRFkaSkJHG5XHqMbEhqcywoKJDIyEgREVEURebOnStl\nZWW6zGxETeWYmpoq58+f/+K4d+/eyezZs6W6ulpqa2tlwYIFUlVVpcfIhqM2Q5fLJQ6HQ2pqaqSx\nsVGcTqc8fPhQj5ENSW2OH128eFGWLl0qqamp3hzT8NqSo1Yd06mvtCdNmoSxY8cCAH788UfU1tZC\nURQcOnQIMTEx2Lt3LwCgoqICLpcLo0aNAgDs27dPt5mNSG2Odrsd9fX1aGhogKIosFqtsNlseo5u\nKM3l+LVbt25hzJgxsNvd3zQgKCgIN27cwMyZM706rxGpzdBmsyE7Oxs9e/YEAPTu3RuvX7/26qxG\npjZHAGhoaMDBgwexdu1a5ObmenNMw1Obo5Yd06l32j4+PvD39wcAnD59GtOmTUNxcTEePHiAefPm\neY4rKSlBr169sHnzZkRFRSEzM1OniY1JbY4DBgzA3Llz4XA44HA4EBUV5fmiSU3n6OPjg+PHj2PZ\nsmVISkpCZWUlKioq0LdvX895ffv2RXl5uV5jG4raDAF4/u4VFBSgpKQE48aN021uo2lLjocPH0Z0\ndDT/LTdBbY6adky7nhswidzcXHE6nVJdXS3x8fHy7NkzERFxOBwiInLz5k0JCQmRyspKcblcsnDh\nQiksLNRzZENqLcfi4mJZunSpuFwuqa6ulvnz50tFRYWeIxvS5zleunRJ7t27JyIihw8flrS0NMnO\nzpYdO3Z4jt+3b5+cPHlSr3ENqbUMPyoqKpKwsDDPx+lLreVYVFQkq1evFhGRy5cv8+nxZrSWo5Yd\n06mvtAH3C6UOHTqEjIwMuFwuPHnyBJs2bUJERATKysoQGxuLfv36YdiwYejTpw9sNhsmTJiAhw8f\n6j26oajJ8fbt2xg3bhxsNhvsdjuGDx+OwsJCvUc3lM9ztNvtCA4OxsiRIwEAM2fORGFhIQIDA1FR\nUeE5p6ysDIGBgXqNbDhqMgSA0tJSJCYmYteuXZ6P0ydqcszLy8OLFy8QERGBtLQ05OXlISMjQ+fJ\njUVNjpp2jJb/2zCa6upqCQsLa/Zq7+MVoohIZGSkVFVViaIoEhkZKffv3/fWmIanNsfbt29LRESE\nKIoiDQ0NsmDBAnn+/Lk3RzW0pnJct26dFBcXi4jI8ePHZfv27VJbWyuzZs2SN2/eyNu3bz0vSiP1\nGYqIrFy5Uq5evarLnEbXlhw/4pX2t9qSo1Yd06lfiJaTk4Oqqips2LDB83u7d+/GwIEDvzl2y5Yt\niI+Ph8ViQUhICEaMGOHNUQ1NbY6jR4/G1KlTERMTAwBwOp0YNGiQV2c1sqZyXLJkCTZs2ACbzQZ/\nf3/s3LkTfn5+SE5ORlxcHCwWCxITEz0vSuvq1GZYVFSEa9euIT093XPc8uXLERoaqsfYhqM2R2pZ\nW3LUqmP4rTmJiIhMotPvtImIiDoLljYREZFJsLSJiIhMgqVNRERkEixtIiIik2BpExERmQRLm4iI\nyCRY2kRERCbxf8E7uoCEWBmpAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e169160>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "t_WbFhAtucYT",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 12141
+        },
+        "outputId": "8fa96e00-f7e1-42b4-9abf-152545334005"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=35000,interval=50)"
+      ],
+      "execution_count": 29,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 6.4734254\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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Fac8vGAJGoD19CluRIiTODCflra4y/KiDZeiN94iICDw8PAAIDw/Hz8+PyMhI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\nAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e13cda0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "FC9Sb6F6ulVV",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 17181
+        },
+        "outputId": "e5597868-7823-473b-a411-684b418d9753"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=50000,interval=50)"
+      ],
+      "execution_count": 30,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Loss after epoch 35000 is 6.7498674\n",
+            "Loss after epoch 35050 is 6.736341\n",
+            "Loss after epoch 35100 is 6.7228174\n",
+            "Loss after epoch 35150 is 6.7093277\n",
+            "Loss after epoch 35200 is 6.6958494\n",
+            "Loss after epoch 35250 is 6.6824474\n",
+            "Loss after epoch 35300 is 6.669072\n",
+            "Loss after epoch 35350 is 6.6557093\n",
+            "Loss after epoch 35400 is 6.6423593\n",
+            "Loss after epoch 35450 is 6.629055\n",
+            "Loss after epoch 35500 is 6.6158056\n",
+            "Loss after epoch 35550 is 6.602567\n",
+            "Loss after epoch 35600 is 6.589341\n",
+            "Loss after epoch 35650 is 6.576157\n",
+            "Loss after epoch 35700 is 6.56305\n",
+            "Loss after epoch 35750 is 6.54993\n",
+            "Loss after epoch 35800 is 6.536834\n",
+            "Loss after epoch 35850 is 6.5237727\n",
+            "Loss after epoch 35900 is 6.510758\n",
+            "Loss after epoch 35950 is 6.497785\n",
+            "Loss after epoch 36000 is 6.484812\n",
+            "Loss after epoch 36050 is 6.471871\n",
+            "Loss after epoch 36100 is 6.458971\n",
+            "Loss after epoch 36150 is 6.446119\n",
+            "Loss after epoch 36200 is 6.4332905\n",
+            "Loss after epoch 36250 is 6.420462\n",
+            "Loss after epoch 36300 is 6.4076543\n",
+            "Loss after epoch 36350 is 6.39493\n",
+            "Loss after epoch 36400 is 6.382219\n",
+            "Loss after epoch 36450 is 6.369523\n",
+            "Loss after epoch 36500 is 6.3568425\n",
+            "Loss after epoch 36550 is 6.3442206\n",
+            "Loss after epoch 36600 is 6.3316355\n",
+            "Loss after epoch 36650 is 6.319064\n",
+            "Loss after epoch 36700 is 6.306503\n",
+            "Loss after epoch 36750 is 6.2939878\n",
+            "Loss after epoch 36800 is 6.281519\n",
+            "Loss after epoch 36850 is 6.2690606\n",
+            "Loss after epoch 36900 is 6.25664\n",
+            "Loss after epoch 36950 is 6.2442183\n",
+            "Loss after epoch 37000 is 6.231861\n",
+            "Loss after epoch 37050 is 6.219538\n",
+            "Loss after epoch 37100 is 6.207241\n",
+            "Loss after epoch 37150 is 6.194936\n",
+            "Loss after epoch 37200 is 6.1826687\n",
+            "Loss after epoch 37250 is 6.170473\n",
+            "Loss after epoch 37300 is 6.158289\n",
+            "Loss after epoch 37350 is 6.146099\n",
+            "Loss after epoch 37400 is 6.133947\n",
+            "Loss after epoch 37450 is 6.12185\n",
+            "Loss after epoch 37500 is 6.10978\n",
+            "Loss after epoch 37550 is 6.097728\n",
+            "Loss after epoch 37600 is 6.085694\n",
+            "Loss after epoch 37650 is 6.0736694\n",
+            "Loss after epoch 37700 is 6.0617213\n",
+            "Loss after epoch 37750 is 6.049802\n",
+            "Loss after epoch 37800 is 6.037884\n",
+            "Loss after epoch 37850 is 6.025973\n",
+            "Loss after epoch 37900 is 6.014111\n",
+            "Loss after epoch 37950 is 6.002307\n",
+            "Loss after epoch 38000 is 5.990502\n",
+            "Loss after epoch 38050 is 5.978728\n",
+            "Loss after epoch 38100 is 5.9669485\n",
+            "Loss after epoch 38150 is 5.9552464\n",
+            "Loss after epoch 38200 is 5.9435773\n",
+            "Loss after epoch 38250 is 5.931912\n",
+            "Loss after epoch 38300 is 5.920269\n",
+            "Loss after epoch 38350 is 5.908628\n",
+            "Loss after epoch 38400 is 5.897071\n",
+            "Loss after epoch 38450 is 5.8855247\n",
+            "Loss after epoch 38500 is 5.873994\n",
+            "Loss after epoch 38550 is 5.862472\n",
+            "Loss after epoch 38600 is 5.851006\n",
+            "Loss after epoch 38650 is 5.8395667\n",
+            "Loss after epoch 38700 is 5.828153\n",
+            "Loss after epoch 38750 is 5.8167434\n",
+            "Loss after epoch 38800 is 5.805351\n",
+            "Loss after epoch 38850 is 5.794033\n",
+            "Loss after epoch 38900 is 5.7827215\n",
+            "Loss after epoch 38950 is 5.7714443\n",
+            "Loss after epoch 39000 is 5.760165\n",
+            "Loss after epoch 39050 is 5.748919\n",
+            "Loss after epoch 39100 is 5.737723\n",
+            "Loss after epoch 39150 is 5.7265515\n",
+            "Loss after epoch 39200 is 5.7153926\n",
+            "Loss after epoch 39250 is 5.7042456\n",
+            "Loss after epoch 39300 is 5.6931334\n",
+            "Loss after epoch 39350 is 5.6820674\n",
+            "Loss after epoch 39400 is 5.6710277\n",
+            "Loss after epoch 39450 is 5.6599975\n",
+            "Loss after epoch 39500 is 5.6489773\n",
+            "Loss after epoch 39550 is 5.6379986\n",
+            "Loss after epoch 39600 is 5.6270638\n",
+            "Loss after epoch 39650 is 5.6161437\n",
+            "Loss after epoch 39700 is 5.605234\n",
+            "Loss after epoch 39750 is 5.594359\n",
+            "Loss after epoch 39800 is 5.583513\n",
+            "Loss after epoch 39850 is 5.5727015\n",
+            "Loss after epoch 39900 is 5.5619187\n",
+            "Loss after epoch 39950 is 5.5511293\n",
+            "Loss after epoch 40000 is 5.5403595\n",
+            "Loss after epoch 40050 is 5.5296636\n",
+            "Loss after epoch 40100 is 5.5189734\n",
+            "Loss after epoch 40150 is 5.50831\n",
+            "Loss after epoch 40200 is 5.4976435\n",
+            "Loss after epoch 40250 is 5.4870124\n",
+            "Loss after epoch 40300 is 5.4764233\n",
+            "Loss after epoch 40350 is 5.465869\n",
+            "Loss after epoch 40400 is 5.4553204\n",
+            "Loss after epoch 40450 is 5.4447737\n",
+            "Loss after epoch 40500 is 5.434271\n",
+            "Loss after epoch 40550 is 5.4238167\n",
+            "Loss after epoch 40600 is 5.413378\n",
+            "Loss after epoch 40650 is 5.4029517\n",
+            "Loss after epoch 40700 is 5.3925357\n",
+            "Loss after epoch 40750 is 5.3821487\n",
+            "Loss after epoch 40800 is 5.3718243\n",
+            "Loss after epoch 40850 is 5.3615\n",
+            "Loss after epoch 40900 is 5.351192\n",
+            "Loss after epoch 40950 is 5.3408957\n",
+            "Loss after epoch 41000 is 5.3306355\n",
+            "Loss after epoch 41050 is 5.320417\n",
+            "Loss after epoch 41100 is 5.3102283\n",
+            "Loss after epoch 41150 is 5.3000364\n",
+            "Loss after epoch 41200 is 5.2898607\n",
+            "Loss after epoch 41250 is 5.27973\n",
+            "Loss after epoch 41300 is 5.269627\n",
+            "Loss after epoch 41350 is 5.259549\n",
+            "Loss after epoch 41400 is 5.249473\n",
+            "Loss after epoch 41450 is 5.2394214\n",
+            "Loss after epoch 41500 is 5.229395\n",
+            "Loss after epoch 41550 is 5.219424\n",
+            "Loss after epoch 41600 is 5.2094607\n",
+            "Loss after epoch 41650 is 5.1995144\n",
+            "Loss after epoch 41700 is 5.189558\n",
+            "Loss after epoch 41750 is 5.1796594\n",
+            "Loss after epoch 41800 is 5.169802\n",
+            "Loss after epoch 41850 is 5.159956\n",
+            "Loss after epoch 41900 is 5.15012\n",
+            "Loss after epoch 41950 is 5.140296\n",
+            "Loss after epoch 42000 is 5.130499\n",
+            "Loss after epoch 42050 is 5.120755\n",
+            "Loss after epoch 42100 is 5.1110187\n",
+            "Loss after epoch 42150 is 5.1013103\n",
+            "Loss after epoch 42200 is 5.0915947\n",
+            "Loss after epoch 42250 is 5.0819106\n",
+            "Loss after epoch 42300 is 5.072277\n",
+            "Loss after epoch 42350 is 5.0626636\n",
+            "Loss after epoch 42400 is 5.053055\n",
+            "Loss after epoch 42450 is 5.0434656\n",
+            "Loss after epoch 42500 is 5.0338855\n",
+            "Loss after epoch 42550 is 5.0243716\n",
+            "Loss after epoch 42600 is 5.0148754\n",
+            "Loss after epoch 42650 is 5.0053706\n",
+            "Loss after epoch 42700 is 4.9958925\n",
+            "Loss after epoch 42750 is 4.9864287\n",
+            "Loss after epoch 42800 is 4.977026\n",
+            "Loss after epoch 42850 is 4.9676194\n",
+            "Loss after epoch 42900 is 4.958237\n",
+            "Loss after epoch 42950 is 4.94887\n",
+            "Loss after epoch 43000 is 4.9395165\n",
+            "Loss after epoch 43050 is 4.9302077\n",
+            "Loss after epoch 43100 is 4.920943\n",
+            "Loss after epoch 43150 is 4.9116707\n",
+            "Loss after epoch 43200 is 4.9024096\n",
+            "Loss after epoch 43250 is 4.8931603\n",
+            "Loss after epoch 43300 is 4.8839593\n",
+            "Loss after epoch 43350 is 4.874786\n",
+            "Loss after epoch 43400 is 4.8656197\n",
+            "Loss after epoch 43450 is 4.856484\n",
+            "Loss after epoch 43500 is 4.8473415\n",
+            "Loss after epoch 43550 is 4.8382344\n",
+            "Loss after epoch 43600 is 4.8291783\n",
+            "Loss after epoch 43650 is 4.8201203\n",
+            "Loss after epoch 43700 is 4.811085\n",
+            "Loss after epoch 43750 is 4.802051\n",
+            "Loss after epoch 43800 is 4.793043\n",
+            "Loss after epoch 43850 is 4.7840962\n",
+            "Loss after epoch 43900 is 4.7751417\n",
+            "Loss after epoch 43950 is 4.7662163\n",
+            "Loss after epoch 44000 is 4.757295\n",
+            "Loss after epoch 44050 is 4.74839\n",
+            "Loss after epoch 44100 is 4.739529\n",
+            "Loss after epoch 44150 is 4.730694\n",
+            "Loss after epoch 44200 is 4.7218733\n",
+            "Loss after epoch 44250 is 4.7130585\n",
+            "Loss after epoch 44300 is 4.7042527\n",
+            "Loss after epoch 44350 is 4.6954947\n",
+            "Loss after epoch 44400 is 4.686761\n",
+            "Loss after epoch 44450 is 4.6780453\n",
+            "Loss after epoch 44500 is 4.6693335\n",
+            "Loss after epoch 44550 is 4.660631\n",
+            "Loss after epoch 44600 is 4.6519604\n",
+            "Loss after epoch 44650 is 4.643334\n",
+            "Loss after epoch 44700 is 4.634729\n",
+            "Loss after epoch 44750 is 4.626118\n",
+            "Loss after epoch 44800 is 4.6175213\n",
+            "Loss after epoch 44850 is 4.608947\n",
+            "Loss after epoch 44900 is 4.600414\n",
+            "Loss after epoch 44950 is 4.591895\n",
+            "Loss after epoch 45000 is 4.583406\n",
+            "Loss after epoch 45050 is 4.5749216\n",
+            "Loss after epoch 45100 is 4.566434\n",
+            "Loss after epoch 45150 is 4.557984\n",
+            "Loss after epoch 45200 is 4.5495834\n",
+            "Loss after epoch 45250 is 4.5411925\n",
+            "Loss after epoch 45300 is 4.5327992\n",
+            "Loss after epoch 45350 is 4.5244207\n",
+            "Loss after epoch 45400 is 4.5160594\n",
+            "Loss after epoch 45450 is 4.507754\n",
+            "Loss after epoch 45500 is 4.4994583\n",
+            "Loss after epoch 45550 is 4.491178\n",
+            "Loss after epoch 45600 is 4.4829006\n",
+            "Loss after epoch 45650 is 4.4746375\n",
+            "Loss after epoch 45700 is 4.4663954\n",
+            "Loss after epoch 45750 is 4.4582067\n",
+            "Loss after epoch 45800 is 4.450019\n",
+            "Loss after epoch 45850 is 4.4418554\n",
+            "Loss after epoch 45900 is 4.4336944\n",
+            "Loss after epoch 45950 is 4.425536\n",
+            "Loss after epoch 46000 is 4.4174347\n",
+            "Loss after epoch 46050 is 4.409361\n",
+            "Loss after epoch 46100 is 4.401283\n",
+            "Loss after epoch 46150 is 4.393225\n",
+            "Loss after epoch 46200 is 4.3851695\n",
+            "Loss after epoch 46250 is 4.3771367\n",
+            "Loss after epoch 46300 is 4.369162\n",
+            "Loss after epoch 46350 is 4.3611794\n",
+            "Loss after epoch 46400 is 4.3532248\n",
+            "Loss after epoch 46450 is 4.34527\n",
+            "Loss after epoch 46500 is 4.3373346\n",
+            "Loss after epoch 46550 is 4.329418\n",
+            "Loss after epoch 46600 is 4.321548\n",
+            "Loss after epoch 46650 is 4.3136845\n",
+            "Loss after epoch 46700 is 4.305833\n",
+            "Loss after epoch 46750 is 4.2979856\n",
+            "Loss after epoch 46800 is 4.290157\n",
+            "Loss after epoch 46850 is 4.282368\n",
+            "Loss after epoch 46900 is 4.2746058\n",
+            "Loss after epoch 46950 is 4.2668395\n",
+            "Loss after epoch 47000 is 4.2591057\n",
+            "Loss after epoch 47050 is 4.2513623\n",
+            "Loss after epoch 47100 is 4.243639\n",
+            "Loss after epoch 47150 is 4.2359667\n",
+            "Loss after epoch 47200 is 4.2283144\n",
+            "Loss after epoch 47250 is 4.2206597\n",
+            "Loss after epoch 47300 is 4.213019\n",
+            "Loss after epoch 47350 is 4.2053847\n",
+            "Loss after epoch 47400 is 4.197782\n",
+            "Loss after epoch 47450 is 4.190225\n",
+            "Loss after epoch 47500 is 4.1826615\n",
+            "Loss after epoch 47550 is 4.175118\n",
+            "Loss after epoch 47600 is 4.167579\n",
+            "Loss after epoch 47650 is 4.160053\n",
+            "Loss after epoch 47700 is 4.1525626\n",
+            "Loss after epoch 47750 is 4.1451054\n",
+            "Loss after epoch 47800 is 4.137654\n",
+            "Loss after epoch 47850 is 4.130212\n",
+            "Loss after epoch 47900 is 4.122782\n",
+            "Loss after epoch 47950 is 4.1153445\n",
+            "Loss after epoch 48000 is 4.107983\n",
+            "Loss after epoch 48050 is 4.100624\n",
+            "Loss after epoch 48100 is 4.093271\n",
+            "Loss after epoch 48150 is 4.0859313\n",
+            "Loss after epoch 48200 is 4.078599\n",
+            "Loss after epoch 48250 is 4.0712757\n",
+            "Loss after epoch 48300 is 4.0640044\n",
+            "Loss after epoch 48350 is 4.056761\n",
+            "Loss after epoch 48400 is 4.0495076\n",
+            "Loss after epoch 48450 is 4.042268\n",
+            "Loss after epoch 48500 is 4.0350304\n",
+            "Loss after epoch 48550 is 4.0278254\n",
+            "Loss after epoch 48600 is 4.020656\n",
+            "Loss after epoch 48650 is 4.0135055\n",
+            "Loss after epoch 48700 is 4.006352\n",
+            "Loss after epoch 48750 is 3.999221\n",
+            "Loss after epoch 48800 is 3.992085\n",
+            "Loss after epoch 48850 is 3.9849706\n",
+            "Loss after epoch 48900 is 3.9779043\n",
+            "Loss after epoch 48950 is 3.9708493\n",
+            "Loss after epoch 49000 is 3.9638073\n",
+            "Loss after epoch 49050 is 3.956756\n",
+            "Loss after epoch 49100 is 3.9497316\n",
+            "Loss after epoch 49150 is 3.9427223\n",
+            "Loss after epoch 49200 is 3.9357584\n",
+            "Loss after epoch 49250 is 3.9288023\n",
+            "Loss after epoch 49300 is 3.9218378\n",
+            "Loss after epoch 49350 is 3.914897\n",
+            "Loss after epoch 49400 is 3.9079638\n",
+            "Loss after epoch 49450 is 3.9010508\n",
+            "Loss after epoch 49500 is 3.8941777\n",
+            "Loss after epoch 49550 is 3.887318\n",
+            "Loss after epoch 49600 is 3.8804762\n",
+            "Loss after epoch 49650 is 3.8736296\n",
+            "Loss after epoch 49700 is 3.86679\n",
+            "Loss after epoch 49750 is 3.859968\n",
+            "Loss after epoch 49800 is 3.8531907\n",
+            "Loss after epoch 49850 is 3.8464336\n",
+            "Loss after epoch 49900 is 3.8396757\n",
+            "Loss after epoch 49950 is 3.8329346\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 3.4775605\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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Ya2rjenCfjGYtTLtx1ahpuZpEjkhoCyFELohPjefD3YP55cZeKherwqpOG6hX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\nK8HQJiIishIMbSIiIivx/yYH+2PAD+MTAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e3b48d0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "THEq_zPuux0T",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 18861
+        },
+        "outputId": "0d286b2a-ca2d-4dbb-85c7-db65114f7ad6"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=55000,interval=50)"
+      ],
+      "execution_count": 31,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Loss after epoch 35000 is 6.7498674\n",
+            "Loss after epoch 35050 is 6.736341\n",
+            "Loss after epoch 35100 is 6.7228174\n",
+            "Loss after epoch 35150 is 6.7093277\n",
+            "Loss after epoch 35200 is 6.6958494\n",
+            "Loss after epoch 35250 is 6.6824474\n",
+            "Loss after epoch 35300 is 6.669072\n",
+            "Loss after epoch 35350 is 6.6557093\n",
+            "Loss after epoch 35400 is 6.6423593\n",
+            "Loss after epoch 35450 is 6.629055\n",
+            "Loss after epoch 35500 is 6.6158056\n",
+            "Loss after epoch 35550 is 6.602567\n",
+            "Loss after epoch 35600 is 6.589341\n",
+            "Loss after epoch 35650 is 6.576157\n",
+            "Loss after epoch 35700 is 6.56305\n",
+            "Loss after epoch 35750 is 6.54993\n",
+            "Loss after epoch 35800 is 6.536834\n",
+            "Loss after epoch 35850 is 6.5237727\n",
+            "Loss after epoch 35900 is 6.510758\n",
+            "Loss after epoch 35950 is 6.497785\n",
+            "Loss after epoch 36000 is 6.484812\n",
+            "Loss after epoch 36050 is 6.471871\n",
+            "Loss after epoch 36100 is 6.458971\n",
+            "Loss after epoch 36150 is 6.446119\n",
+            "Loss after epoch 36200 is 6.4332905\n",
+            "Loss after epoch 36250 is 6.420462\n",
+            "Loss after epoch 36300 is 6.4076543\n",
+            "Loss after epoch 36350 is 6.39493\n",
+            "Loss after epoch 36400 is 6.382219\n",
+            "Loss after epoch 36450 is 6.369523\n",
+            "Loss after epoch 36500 is 6.3568425\n",
+            "Loss after epoch 36550 is 6.3442206\n",
+            "Loss after epoch 36600 is 6.3316355\n",
+            "Loss after epoch 36650 is 6.319064\n",
+            "Loss after epoch 36700 is 6.306503\n",
+            "Loss after epoch 36750 is 6.2939878\n",
+            "Loss after epoch 36800 is 6.281519\n",
+            "Loss after epoch 36850 is 6.2690606\n",
+            "Loss after epoch 36900 is 6.25664\n",
+            "Loss after epoch 36950 is 6.2442183\n",
+            "Loss after epoch 37000 is 6.231861\n",
+            "Loss after epoch 37050 is 6.219538\n",
+            "Loss after epoch 37100 is 6.207241\n",
+            "Loss after epoch 37150 is 6.194936\n",
+            "Loss after epoch 37200 is 6.1826687\n",
+            "Loss after epoch 37250 is 6.170473\n",
+            "Loss after epoch 37300 is 6.158289\n",
+            "Loss after epoch 37350 is 6.146099\n",
+            "Loss after epoch 37400 is 6.133947\n",
+            "Loss after epoch 37450 is 6.12185\n",
+            "Loss after epoch 37500 is 6.10978\n",
+            "Loss after epoch 37550 is 6.097728\n",
+            "Loss after epoch 37600 is 6.085694\n",
+            "Loss after epoch 37650 is 6.0736694\n",
+            "Loss after epoch 37700 is 6.0617213\n",
+            "Loss after epoch 37750 is 6.049802\n",
+            "Loss after epoch 37800 is 6.037884\n",
+            "Loss after epoch 37850 is 6.025973\n",
+            "Loss after epoch 37900 is 6.014111\n",
+            "Loss after epoch 37950 is 6.002307\n",
+            "Loss after epoch 38000 is 5.990502\n",
+            "Loss after epoch 38050 is 5.978728\n",
+            "Loss after epoch 38100 is 5.9669485\n",
+            "Loss after epoch 38150 is 5.9552464\n",
+            "Loss after epoch 38200 is 5.9435773\n",
+            "Loss after epoch 38250 is 5.931912\n",
+            "Loss after epoch 38300 is 5.920269\n",
+            "Loss after epoch 38350 is 5.908628\n",
+            "Loss after epoch 38400 is 5.897071\n",
+            "Loss after epoch 38450 is 5.8855247\n",
+            "Loss after epoch 38500 is 5.873994\n",
+            "Loss after epoch 38550 is 5.862472\n",
+            "Loss after epoch 38600 is 5.851006\n",
+            "Loss after epoch 38650 is 5.8395667\n",
+            "Loss after epoch 38700 is 5.828153\n",
+            "Loss after epoch 38750 is 5.8167434\n",
+            "Loss after epoch 38800 is 5.805351\n",
+            "Loss after epoch 38850 is 5.794033\n",
+            "Loss after epoch 38900 is 5.7827215\n",
+            "Loss after epoch 38950 is 5.7714443\n",
+            "Loss after epoch 39000 is 5.760165\n",
+            "Loss after epoch 39050 is 5.748919\n",
+            "Loss after epoch 39100 is 5.737723\n",
+            "Loss after epoch 39150 is 5.7265515\n",
+            "Loss after epoch 39200 is 5.7153926\n",
+            "Loss after epoch 39250 is 5.7042456\n",
+            "Loss after epoch 39300 is 5.6931334\n",
+            "Loss after epoch 39350 is 5.6820674\n",
+            "Loss after epoch 39400 is 5.6710277\n",
+            "Loss after epoch 39450 is 5.6599975\n",
+            "Loss after epoch 39500 is 5.6489773\n",
+            "Loss after epoch 39550 is 5.6379986\n",
+            "Loss after epoch 39600 is 5.6270638\n",
+            "Loss after epoch 39650 is 5.6161437\n",
+            "Loss after epoch 39700 is 5.605234\n",
+            "Loss after epoch 39750 is 5.594359\n",
+            "Loss after epoch 39800 is 5.583513\n",
+            "Loss after epoch 39850 is 5.5727015\n",
+            "Loss after epoch 39900 is 5.5619187\n",
+            "Loss after epoch 39950 is 5.5511293\n",
+            "Loss after epoch 40000 is 5.5403595\n",
+            "Loss after epoch 40050 is 5.5296636\n",
+            "Loss after epoch 40100 is 5.5189734\n",
+            "Loss after epoch 40150 is 5.50831\n",
+            "Loss after epoch 40200 is 5.4976435\n",
+            "Loss after epoch 40250 is 5.4870124\n",
+            "Loss after epoch 40300 is 5.4764233\n",
+            "Loss after epoch 40350 is 5.465869\n",
+            "Loss after epoch 40400 is 5.4553204\n",
+            "Loss after epoch 40450 is 5.4447737\n",
+            "Loss after epoch 40500 is 5.434271\n",
+            "Loss after epoch 40550 is 5.4238167\n",
+            "Loss after epoch 40600 is 5.413378\n",
+            "Loss after epoch 40650 is 5.4029517\n",
+            "Loss after epoch 40700 is 5.3925357\n",
+            "Loss after epoch 40750 is 5.3821487\n",
+            "Loss after epoch 40800 is 5.3718243\n",
+            "Loss after epoch 40850 is 5.3615\n",
+            "Loss after epoch 40900 is 5.351192\n",
+            "Loss after epoch 40950 is 5.3408957\n",
+            "Loss after epoch 41000 is 5.3306355\n",
+            "Loss after epoch 41050 is 5.320417\n",
+            "Loss after epoch 41100 is 5.3102283\n",
+            "Loss after epoch 41150 is 5.3000364\n",
+            "Loss after epoch 41200 is 5.2898607\n",
+            "Loss after epoch 41250 is 5.27973\n",
+            "Loss after epoch 41300 is 5.269627\n",
+            "Loss after epoch 41350 is 5.259549\n",
+            "Loss after epoch 41400 is 5.249473\n",
+            "Loss after epoch 41450 is 5.2394214\n",
+            "Loss after epoch 41500 is 5.229395\n",
+            "Loss after epoch 41550 is 5.219424\n",
+            "Loss after epoch 41600 is 5.2094607\n",
+            "Loss after epoch 41650 is 5.1995144\n",
+            "Loss after epoch 41700 is 5.189558\n",
+            "Loss after epoch 41750 is 5.1796594\n",
+            "Loss after epoch 41800 is 5.169802\n",
+            "Loss after epoch 41850 is 5.159956\n",
+            "Loss after epoch 41900 is 5.15012\n",
+            "Loss after epoch 41950 is 5.140296\n",
+            "Loss after epoch 42000 is 5.130499\n",
+            "Loss after epoch 42050 is 5.120755\n",
+            "Loss after epoch 42100 is 5.1110187\n",
+            "Loss after epoch 42150 is 5.1013103\n",
+            "Loss after epoch 42200 is 5.0915947\n",
+            "Loss after epoch 42250 is 5.0819106\n",
+            "Loss after epoch 42300 is 5.072277\n",
+            "Loss after epoch 42350 is 5.0626636\n",
+            "Loss after epoch 42400 is 5.053055\n",
+            "Loss after epoch 42450 is 5.0434656\n",
+            "Loss after epoch 42500 is 5.0338855\n",
+            "Loss after epoch 42550 is 5.0243716\n",
+            "Loss after epoch 42600 is 5.0148754\n",
+            "Loss after epoch 42650 is 5.0053706\n",
+            "Loss after epoch 42700 is 4.9958925\n",
+            "Loss after epoch 42750 is 4.9864287\n",
+            "Loss after epoch 42800 is 4.977026\n",
+            "Loss after epoch 42850 is 4.9676194\n",
+            "Loss after epoch 42900 is 4.958237\n",
+            "Loss after epoch 42950 is 4.94887\n",
+            "Loss after epoch 43000 is 4.9395165\n",
+            "Loss after epoch 43050 is 4.9302077\n",
+            "Loss after epoch 43100 is 4.920943\n",
+            "Loss after epoch 43150 is 4.9116707\n",
+            "Loss after epoch 43200 is 4.9024096\n",
+            "Loss after epoch 43250 is 4.8931603\n",
+            "Loss after epoch 43300 is 4.8839593\n",
+            "Loss after epoch 43350 is 4.874786\n",
+            "Loss after epoch 43400 is 4.8656197\n",
+            "Loss after epoch 43450 is 4.856484\n",
+            "Loss after epoch 43500 is 4.8473415\n",
+            "Loss after epoch 43550 is 4.8382344\n",
+            "Loss after epoch 43600 is 4.8291783\n",
+            "Loss after epoch 43650 is 4.8201203\n",
+            "Loss after epoch 43700 is 4.811085\n",
+            "Loss after epoch 43750 is 4.802051\n",
+            "Loss after epoch 43800 is 4.793043\n",
+            "Loss after epoch 43850 is 4.7840962\n",
+            "Loss after epoch 43900 is 4.7751417\n",
+            "Loss after epoch 43950 is 4.7662163\n",
+            "Loss after epoch 44000 is 4.757295\n",
+            "Loss after epoch 44050 is 4.74839\n",
+            "Loss after epoch 44100 is 4.739529\n",
+            "Loss after epoch 44150 is 4.730694\n",
+            "Loss after epoch 44200 is 4.7218733\n",
+            "Loss after epoch 44250 is 4.7130585\n",
+            "Loss after epoch 44300 is 4.7042527\n",
+            "Loss after epoch 44350 is 4.6954947\n",
+            "Loss after epoch 44400 is 4.686761\n",
+            "Loss after epoch 44450 is 4.6780453\n",
+            "Loss after epoch 44500 is 4.6693335\n",
+            "Loss after epoch 44550 is 4.660631\n",
+            "Loss after epoch 44600 is 4.6519604\n",
+            "Loss after epoch 44650 is 4.643334\n",
+            "Loss after epoch 44700 is 4.634729\n",
+            "Loss after epoch 44750 is 4.626118\n",
+            "Loss after epoch 44800 is 4.6175213\n",
+            "Loss after epoch 44850 is 4.608947\n",
+            "Loss after epoch 44900 is 4.600414\n",
+            "Loss after epoch 44950 is 4.591895\n",
+            "Loss after epoch 45000 is 4.583406\n",
+            "Loss after epoch 45050 is 4.5749216\n",
+            "Loss after epoch 45100 is 4.566434\n",
+            "Loss after epoch 45150 is 4.557984\n",
+            "Loss after epoch 45200 is 4.5495834\n",
+            "Loss after epoch 45250 is 4.5411925\n",
+            "Loss after epoch 45300 is 4.5327992\n",
+            "Loss after epoch 45350 is 4.5244207\n",
+            "Loss after epoch 45400 is 4.5160594\n",
+            "Loss after epoch 45450 is 4.507754\n",
+            "Loss after epoch 45500 is 4.4994583\n",
+            "Loss after epoch 45550 is 4.491178\n",
+            "Loss after epoch 45600 is 4.4829006\n",
+            "Loss after epoch 45650 is 4.4746375\n",
+            "Loss after epoch 45700 is 4.4663954\n",
+            "Loss after epoch 45750 is 4.4582067\n",
+            "Loss after epoch 45800 is 4.450019\n",
+            "Loss after epoch 45850 is 4.4418554\n",
+            "Loss after epoch 45900 is 4.4336944\n",
+            "Loss after epoch 45950 is 4.425536\n",
+            "Loss after epoch 46000 is 4.4174347\n",
+            "Loss after epoch 46050 is 4.409361\n",
+            "Loss after epoch 46100 is 4.401283\n",
+            "Loss after epoch 46150 is 4.393225\n",
+            "Loss after epoch 46200 is 4.3851695\n",
+            "Loss after epoch 46250 is 4.3771367\n",
+            "Loss after epoch 46300 is 4.369162\n",
+            "Loss after epoch 46350 is 4.3611794\n",
+            "Loss after epoch 46400 is 4.3532248\n",
+            "Loss after epoch 46450 is 4.34527\n",
+            "Loss after epoch 46500 is 4.3373346\n",
+            "Loss after epoch 46550 is 4.329418\n",
+            "Loss after epoch 46600 is 4.321548\n",
+            "Loss after epoch 46650 is 4.3136845\n",
+            "Loss after epoch 46700 is 4.305833\n",
+            "Loss after epoch 46750 is 4.2979856\n",
+            "Loss after epoch 46800 is 4.290157\n",
+            "Loss after epoch 46850 is 4.282368\n",
+            "Loss after epoch 46900 is 4.2746058\n",
+            "Loss after epoch 46950 is 4.2668395\n",
+            "Loss after epoch 47000 is 4.2591057\n",
+            "Loss after epoch 47050 is 4.2513623\n",
+            "Loss after epoch 47100 is 4.243639\n",
+            "Loss after epoch 47150 is 4.2359667\n",
+            "Loss after epoch 47200 is 4.2283144\n",
+            "Loss after epoch 47250 is 4.2206597\n",
+            "Loss after epoch 47300 is 4.213019\n",
+            "Loss after epoch 47350 is 4.2053847\n",
+            "Loss after epoch 47400 is 4.197782\n",
+            "Loss after epoch 47450 is 4.190225\n",
+            "Loss after epoch 47500 is 4.1826615\n",
+            "Loss after epoch 47550 is 4.175118\n",
+            "Loss after epoch 47600 is 4.167579\n",
+            "Loss after epoch 47650 is 4.160053\n",
+            "Loss after epoch 47700 is 4.1525626\n",
+            "Loss after epoch 47750 is 4.1451054\n",
+            "Loss after epoch 47800 is 4.137654\n",
+            "Loss after epoch 47850 is 4.130212\n",
+            "Loss after epoch 47900 is 4.122782\n",
+            "Loss after epoch 47950 is 4.1153445\n",
+            "Loss after epoch 48000 is 4.107983\n",
+            "Loss after epoch 48050 is 4.100624\n",
+            "Loss after epoch 48100 is 4.093271\n",
+            "Loss after epoch 48150 is 4.0859313\n",
+            "Loss after epoch 48200 is 4.078599\n",
+            "Loss after epoch 48250 is 4.0712757\n",
+            "Loss after epoch 48300 is 4.0640044\n",
+            "Loss after epoch 48350 is 4.056761\n",
+            "Loss after epoch 48400 is 4.0495076\n",
+            "Loss after epoch 48450 is 4.042268\n",
+            "Loss after epoch 48500 is 4.0350304\n",
+            "Loss after epoch 48550 is 4.0278254\n",
+            "Loss after epoch 48600 is 4.020656\n",
+            "Loss after epoch 48650 is 4.0135055\n",
+            "Loss after epoch 48700 is 4.006352\n",
+            "Loss after epoch 48750 is 3.999221\n",
+            "Loss after epoch 48800 is 3.992085\n",
+            "Loss after epoch 48850 is 3.9849706\n",
+            "Loss after epoch 48900 is 3.9779043\n",
+            "Loss after epoch 48950 is 3.9708493\n",
+            "Loss after epoch 49000 is 3.9638073\n",
+            "Loss after epoch 49050 is 3.956756\n",
+            "Loss after epoch 49100 is 3.9497316\n",
+            "Loss after epoch 49150 is 3.9427223\n",
+            "Loss after epoch 49200 is 3.9357584\n",
+            "Loss after epoch 49250 is 3.9288023\n",
+            "Loss after epoch 49300 is 3.9218378\n",
+            "Loss after epoch 49350 is 3.914897\n",
+            "Loss after epoch 49400 is 3.9079638\n",
+            "Loss after epoch 49450 is 3.9010508\n",
+            "Loss after epoch 49500 is 3.8941777\n",
+            "Loss after epoch 49550 is 3.887318\n",
+            "Loss after epoch 49600 is 3.8804762\n",
+            "Loss after epoch 49650 is 3.8736296\n",
+            "Loss after epoch 49700 is 3.86679\n",
+            "Loss after epoch 49750 is 3.859968\n",
+            "Loss after epoch 49800 is 3.8531907\n",
+            "Loss after epoch 49850 is 3.8464336\n",
+            "Loss after epoch 49900 is 3.8396757\n",
+            "Loss after epoch 49950 is 3.8329346\n",
+            "Loss after epoch 50000 is 3.826188\n",
+            "Loss after epoch 50050 is 3.819452\n",
+            "Loss after epoch 50100 is 3.8127787\n",
+            "Loss after epoch 50150 is 3.8061047\n",
+            "Loss after epoch 50200 is 3.7994502\n",
+            "Loss after epoch 50250 is 3.7928014\n",
+            "Loss after epoch 50300 is 3.786149\n",
+            "Loss after epoch 50350 is 3.7795148\n",
+            "Loss after epoch 50400 is 3.772928\n",
+            "Loss after epoch 50450 is 3.7663581\n",
+            "Loss after epoch 50500 is 3.7597787\n",
+            "Loss after epoch 50550 is 3.7532248\n",
+            "Loss after epoch 50600 is 3.7466762\n",
+            "Loss after epoch 50650 is 3.7401314\n",
+            "Loss after epoch 50700 is 3.7336287\n",
+            "Loss after epoch 50750 is 3.7271445\n",
+            "Loss after epoch 50800 is 3.720672\n",
+            "Loss after epoch 50850 is 3.7142055\n",
+            "Loss after epoch 50900 is 3.7077487\n",
+            "Loss after epoch 50950 is 3.7012937\n",
+            "Loss after epoch 51000 is 3.6948748\n",
+            "Loss after epoch 51050 is 3.6884868\n",
+            "Loss after epoch 51100 is 3.6821003\n",
+            "Loss after epoch 51150 is 3.6757364\n",
+            "Loss after epoch 51200 is 3.669365\n",
+            "Loss after epoch 51250 is 3.6630075\n",
+            "Loss after epoch 51300 is 3.6566591\n",
+            "Loss after epoch 51350 is 3.6503675\n",
+            "Loss after epoch 51400 is 3.6440728\n",
+            "Loss after epoch 51450 is 3.6377995\n",
+            "Loss after epoch 51500 is 3.631519\n",
+            "Loss after epoch 51550 is 3.6252565\n",
+            "Loss after epoch 51600 is 3.61899\n",
+            "Loss after epoch 51650 is 3.612775\n",
+            "Loss after epoch 51700 is 3.6065822\n",
+            "Loss after epoch 51750 is 3.60038\n",
+            "Loss after epoch 51800 is 3.5942025\n",
+            "Loss after epoch 51850 is 3.5880246\n",
+            "Loss after epoch 51900 is 3.5818448\n",
+            "Loss after epoch 51950 is 3.5757139\n",
+            "Loss after epoch 52000 is 3.5696058\n",
+            "Loss after epoch 52050 is 3.5635028\n",
+            "Loss after epoch 52100 is 3.5573943\n",
+            "Loss after epoch 52150 is 3.5513074\n",
+            "Loss after epoch 52200 is 3.545228\n",
+            "Loss after epoch 52250 is 3.5391545\n",
+            "Loss after epoch 52300 is 3.53313\n",
+            "Loss after epoch 52350 is 3.527113\n",
+            "Loss after epoch 52400 is 3.5211177\n",
+            "Loss after epoch 52450 is 3.5151153\n",
+            "Loss after epoch 52500 is 3.509117\n",
+            "Loss after epoch 52550 is 3.50313\n",
+            "Loss after epoch 52600 is 3.4971805\n",
+            "Loss after epoch 52650 is 3.4912496\n",
+            "Loss after epoch 52700 is 3.4853241\n",
+            "Loss after epoch 52750 is 3.4794202\n",
+            "Loss after epoch 52800 is 3.473507\n",
+            "Loss after epoch 52850 is 3.467606\n",
+            "Loss after epoch 52900 is 3.4617238\n",
+            "Loss after epoch 52950 is 3.4558768\n",
+            "Loss after epoch 53000 is 3.4500463\n",
+            "Loss after epoch 53050 is 3.4442122\n",
+            "Loss after epoch 53100 is 3.4383948\n",
+            "Loss after epoch 53150 is 3.4325755\n",
+            "Loss after epoch 53200 is 3.4267745\n",
+            "Loss after epoch 53250 is 3.4209945\n",
+            "Loss after epoch 53300 is 3.4152458\n",
+            "Loss after epoch 53350 is 3.4095082\n",
+            "Loss after epoch 53400 is 3.4037755\n",
+            "Loss after epoch 53450 is 3.398037\n",
+            "Loss after epoch 53500 is 3.392319\n",
+            "Loss after epoch 53550 is 3.386605\n",
+            "Loss after epoch 53600 is 3.3809319\n",
+            "Loss after epoch 53650 is 3.3752744\n",
+            "Loss after epoch 53700 is 3.3696232\n",
+            "Loss after epoch 53750 is 3.3639796\n",
+            "Loss after epoch 53800 is 3.358343\n",
+            "Loss after epoch 53850 is 3.3527122\n",
+            "Loss after epoch 53900 is 3.3470953\n",
+            "Loss after epoch 53950 is 3.3415217\n",
+            "Loss after epoch 54000 is 3.335949\n",
+            "Loss after epoch 54050 is 3.3303862\n",
+            "Loss after epoch 54100 is 3.3248417\n",
+            "Loss after epoch 54150 is 3.3192885\n",
+            "Loss after epoch 54200 is 3.3137465\n",
+            "Loss after epoch 54250 is 3.308233\n",
+            "Loss after epoch 54300 is 3.3027437\n",
+            "Loss after epoch 54350 is 3.2972693\n",
+            "Loss after epoch 54400 is 3.291793\n",
+            "Loss after epoch 54450 is 3.2863352\n",
+            "Loss after epoch 54500 is 3.280871\n",
+            "Loss after epoch 54550 is 3.2754228\n",
+            "Loss after epoch 54600 is 3.2700067\n",
+            "Loss after epoch 54650 is 3.2646015\n",
+            "Loss after epoch 54700 is 3.2592132\n",
+            "Loss after epoch 54750 is 3.2538278\n",
+            "Loss after epoch 54800 is 3.24845\n",
+            "Loss after epoch 54850 is 3.243079\n",
+            "Loss after epoch 54900 is 3.2377062\n",
+            "Loss after epoch 54950 is 3.2323837\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 2.8896182\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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hiw8F4qBxIKxzBG80erNQa1CfO4vzpLHY/bIHs86ZlEVLMAweJpOklDAS2kII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\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57e435898>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "eJPAwCcsu-uw",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 20541
+        },
+        "outputId": "98ed9525-02ac-4979-b772-bcdd727fd5a2"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=60000,interval=50)"
+      ],
+      "execution_count": 32,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Loss after epoch 35000 is 6.7498674\n",
+            "Loss after epoch 35050 is 6.736341\n",
+            "Loss after epoch 35100 is 6.7228174\n",
+            "Loss after epoch 35150 is 6.7093277\n",
+            "Loss after epoch 35200 is 6.6958494\n",
+            "Loss after epoch 35250 is 6.6824474\n",
+            "Loss after epoch 35300 is 6.669072\n",
+            "Loss after epoch 35350 is 6.6557093\n",
+            "Loss after epoch 35400 is 6.6423593\n",
+            "Loss after epoch 35450 is 6.629055\n",
+            "Loss after epoch 35500 is 6.6158056\n",
+            "Loss after epoch 35550 is 6.602567\n",
+            "Loss after epoch 35600 is 6.589341\n",
+            "Loss after epoch 35650 is 6.576157\n",
+            "Loss after epoch 35700 is 6.56305\n",
+            "Loss after epoch 35750 is 6.54993\n",
+            "Loss after epoch 35800 is 6.536834\n",
+            "Loss after epoch 35850 is 6.5237727\n",
+            "Loss after epoch 35900 is 6.510758\n",
+            "Loss after epoch 35950 is 6.497785\n",
+            "Loss after epoch 36000 is 6.484812\n",
+            "Loss after epoch 36050 is 6.471871\n",
+            "Loss after epoch 36100 is 6.458971\n",
+            "Loss after epoch 36150 is 6.446119\n",
+            "Loss after epoch 36200 is 6.4332905\n",
+            "Loss after epoch 36250 is 6.420462\n",
+            "Loss after epoch 36300 is 6.4076543\n",
+            "Loss after epoch 36350 is 6.39493\n",
+            "Loss after epoch 36400 is 6.382219\n",
+            "Loss after epoch 36450 is 6.369523\n",
+            "Loss after epoch 36500 is 6.3568425\n",
+            "Loss after epoch 36550 is 6.3442206\n",
+            "Loss after epoch 36600 is 6.3316355\n",
+            "Loss after epoch 36650 is 6.319064\n",
+            "Loss after epoch 36700 is 6.306503\n",
+            "Loss after epoch 36750 is 6.2939878\n",
+            "Loss after epoch 36800 is 6.281519\n",
+            "Loss after epoch 36850 is 6.2690606\n",
+            "Loss after epoch 36900 is 6.25664\n",
+            "Loss after epoch 36950 is 6.2442183\n",
+            "Loss after epoch 37000 is 6.231861\n",
+            "Loss after epoch 37050 is 6.219538\n",
+            "Loss after epoch 37100 is 6.207241\n",
+            "Loss after epoch 37150 is 6.194936\n",
+            "Loss after epoch 37200 is 6.1826687\n",
+            "Loss after epoch 37250 is 6.170473\n",
+            "Loss after epoch 37300 is 6.158289\n",
+            "Loss after epoch 37350 is 6.146099\n",
+            "Loss after epoch 37400 is 6.133947\n",
+            "Loss after epoch 37450 is 6.12185\n",
+            "Loss after epoch 37500 is 6.10978\n",
+            "Loss after epoch 37550 is 6.097728\n",
+            "Loss after epoch 37600 is 6.085694\n",
+            "Loss after epoch 37650 is 6.0736694\n",
+            "Loss after epoch 37700 is 6.0617213\n",
+            "Loss after epoch 37750 is 6.049802\n",
+            "Loss after epoch 37800 is 6.037884\n",
+            "Loss after epoch 37850 is 6.025973\n",
+            "Loss after epoch 37900 is 6.014111\n",
+            "Loss after epoch 37950 is 6.002307\n",
+            "Loss after epoch 38000 is 5.990502\n",
+            "Loss after epoch 38050 is 5.978728\n",
+            "Loss after epoch 38100 is 5.9669485\n",
+            "Loss after epoch 38150 is 5.9552464\n",
+            "Loss after epoch 38200 is 5.9435773\n",
+            "Loss after epoch 38250 is 5.931912\n",
+            "Loss after epoch 38300 is 5.920269\n",
+            "Loss after epoch 38350 is 5.908628\n",
+            "Loss after epoch 38400 is 5.897071\n",
+            "Loss after epoch 38450 is 5.8855247\n",
+            "Loss after epoch 38500 is 5.873994\n",
+            "Loss after epoch 38550 is 5.862472\n",
+            "Loss after epoch 38600 is 5.851006\n",
+            "Loss after epoch 38650 is 5.8395667\n",
+            "Loss after epoch 38700 is 5.828153\n",
+            "Loss after epoch 38750 is 5.8167434\n",
+            "Loss after epoch 38800 is 5.805351\n",
+            "Loss after epoch 38850 is 5.794033\n",
+            "Loss after epoch 38900 is 5.7827215\n",
+            "Loss after epoch 38950 is 5.7714443\n",
+            "Loss after epoch 39000 is 5.760165\n",
+            "Loss after epoch 39050 is 5.748919\n",
+            "Loss after epoch 39100 is 5.737723\n",
+            "Loss after epoch 39150 is 5.7265515\n",
+            "Loss after epoch 39200 is 5.7153926\n",
+            "Loss after epoch 39250 is 5.7042456\n",
+            "Loss after epoch 39300 is 5.6931334\n",
+            "Loss after epoch 39350 is 5.6820674\n",
+            "Loss after epoch 39400 is 5.6710277\n",
+            "Loss after epoch 39450 is 5.6599975\n",
+            "Loss after epoch 39500 is 5.6489773\n",
+            "Loss after epoch 39550 is 5.6379986\n",
+            "Loss after epoch 39600 is 5.6270638\n",
+            "Loss after epoch 39650 is 5.6161437\n",
+            "Loss after epoch 39700 is 5.605234\n",
+            "Loss after epoch 39750 is 5.594359\n",
+            "Loss after epoch 39800 is 5.583513\n",
+            "Loss after epoch 39850 is 5.5727015\n",
+            "Loss after epoch 39900 is 5.5619187\n",
+            "Loss after epoch 39950 is 5.5511293\n",
+            "Loss after epoch 40000 is 5.5403595\n",
+            "Loss after epoch 40050 is 5.5296636\n",
+            "Loss after epoch 40100 is 5.5189734\n",
+            "Loss after epoch 40150 is 5.50831\n",
+            "Loss after epoch 40200 is 5.4976435\n",
+            "Loss after epoch 40250 is 5.4870124\n",
+            "Loss after epoch 40300 is 5.4764233\n",
+            "Loss after epoch 40350 is 5.465869\n",
+            "Loss after epoch 40400 is 5.4553204\n",
+            "Loss after epoch 40450 is 5.4447737\n",
+            "Loss after epoch 40500 is 5.434271\n",
+            "Loss after epoch 40550 is 5.4238167\n",
+            "Loss after epoch 40600 is 5.413378\n",
+            "Loss after epoch 40650 is 5.4029517\n",
+            "Loss after epoch 40700 is 5.3925357\n",
+            "Loss after epoch 40750 is 5.3821487\n",
+            "Loss after epoch 40800 is 5.3718243\n",
+            "Loss after epoch 40850 is 5.3615\n",
+            "Loss after epoch 40900 is 5.351192\n",
+            "Loss after epoch 40950 is 5.3408957\n",
+            "Loss after epoch 41000 is 5.3306355\n",
+            "Loss after epoch 41050 is 5.320417\n",
+            "Loss after epoch 41100 is 5.3102283\n",
+            "Loss after epoch 41150 is 5.3000364\n",
+            "Loss after epoch 41200 is 5.2898607\n",
+            "Loss after epoch 41250 is 5.27973\n",
+            "Loss after epoch 41300 is 5.269627\n",
+            "Loss after epoch 41350 is 5.259549\n",
+            "Loss after epoch 41400 is 5.249473\n",
+            "Loss after epoch 41450 is 5.2394214\n",
+            "Loss after epoch 41500 is 5.229395\n",
+            "Loss after epoch 41550 is 5.219424\n",
+            "Loss after epoch 41600 is 5.2094607\n",
+            "Loss after epoch 41650 is 5.1995144\n",
+            "Loss after epoch 41700 is 5.189558\n",
+            "Loss after epoch 41750 is 5.1796594\n",
+            "Loss after epoch 41800 is 5.169802\n",
+            "Loss after epoch 41850 is 5.159956\n",
+            "Loss after epoch 41900 is 5.15012\n",
+            "Loss after epoch 41950 is 5.140296\n",
+            "Loss after epoch 42000 is 5.130499\n",
+            "Loss after epoch 42050 is 5.120755\n",
+            "Loss after epoch 42100 is 5.1110187\n",
+            "Loss after epoch 42150 is 5.1013103\n",
+            "Loss after epoch 42200 is 5.0915947\n",
+            "Loss after epoch 42250 is 5.0819106\n",
+            "Loss after epoch 42300 is 5.072277\n",
+            "Loss after epoch 42350 is 5.0626636\n",
+            "Loss after epoch 42400 is 5.053055\n",
+            "Loss after epoch 42450 is 5.0434656\n",
+            "Loss after epoch 42500 is 5.0338855\n",
+            "Loss after epoch 42550 is 5.0243716\n",
+            "Loss after epoch 42600 is 5.0148754\n",
+            "Loss after epoch 42650 is 5.0053706\n",
+            "Loss after epoch 42700 is 4.9958925\n",
+            "Loss after epoch 42750 is 4.9864287\n",
+            "Loss after epoch 42800 is 4.977026\n",
+            "Loss after epoch 42850 is 4.9676194\n",
+            "Loss after epoch 42900 is 4.958237\n",
+            "Loss after epoch 42950 is 4.94887\n",
+            "Loss after epoch 43000 is 4.9395165\n",
+            "Loss after epoch 43050 is 4.9302077\n",
+            "Loss after epoch 43100 is 4.920943\n",
+            "Loss after epoch 43150 is 4.9116707\n",
+            "Loss after epoch 43200 is 4.9024096\n",
+            "Loss after epoch 43250 is 4.8931603\n",
+            "Loss after epoch 43300 is 4.8839593\n",
+            "Loss after epoch 43350 is 4.874786\n",
+            "Loss after epoch 43400 is 4.8656197\n",
+            "Loss after epoch 43450 is 4.856484\n",
+            "Loss after epoch 43500 is 4.8473415\n",
+            "Loss after epoch 43550 is 4.8382344\n",
+            "Loss after epoch 43600 is 4.8291783\n",
+            "Loss after epoch 43650 is 4.8201203\n",
+            "Loss after epoch 43700 is 4.811085\n",
+            "Loss after epoch 43750 is 4.802051\n",
+            "Loss after epoch 43800 is 4.793043\n",
+            "Loss after epoch 43850 is 4.7840962\n",
+            "Loss after epoch 43900 is 4.7751417\n",
+            "Loss after epoch 43950 is 4.7662163\n",
+            "Loss after epoch 44000 is 4.757295\n",
+            "Loss after epoch 44050 is 4.74839\n",
+            "Loss after epoch 44100 is 4.739529\n",
+            "Loss after epoch 44150 is 4.730694\n",
+            "Loss after epoch 44200 is 4.7218733\n",
+            "Loss after epoch 44250 is 4.7130585\n",
+            "Loss after epoch 44300 is 4.7042527\n",
+            "Loss after epoch 44350 is 4.6954947\n",
+            "Loss after epoch 44400 is 4.686761\n",
+            "Loss after epoch 44450 is 4.6780453\n",
+            "Loss after epoch 44500 is 4.6693335\n",
+            "Loss after epoch 44550 is 4.660631\n",
+            "Loss after epoch 44600 is 4.6519604\n",
+            "Loss after epoch 44650 is 4.643334\n",
+            "Loss after epoch 44700 is 4.634729\n",
+            "Loss after epoch 44750 is 4.626118\n",
+            "Loss after epoch 44800 is 4.6175213\n",
+            "Loss after epoch 44850 is 4.608947\n",
+            "Loss after epoch 44900 is 4.600414\n",
+            "Loss after epoch 44950 is 4.591895\n",
+            "Loss after epoch 45000 is 4.583406\n",
+            "Loss after epoch 45050 is 4.5749216\n",
+            "Loss after epoch 45100 is 4.566434\n",
+            "Loss after epoch 45150 is 4.557984\n",
+            "Loss after epoch 45200 is 4.5495834\n",
+            "Loss after epoch 45250 is 4.5411925\n",
+            "Loss after epoch 45300 is 4.5327992\n",
+            "Loss after epoch 45350 is 4.5244207\n",
+            "Loss after epoch 45400 is 4.5160594\n",
+            "Loss after epoch 45450 is 4.507754\n",
+            "Loss after epoch 45500 is 4.4994583\n",
+            "Loss after epoch 45550 is 4.491178\n",
+            "Loss after epoch 45600 is 4.4829006\n",
+            "Loss after epoch 45650 is 4.4746375\n",
+            "Loss after epoch 45700 is 4.4663954\n",
+            "Loss after epoch 45750 is 4.4582067\n",
+            "Loss after epoch 45800 is 4.450019\n",
+            "Loss after epoch 45850 is 4.4418554\n",
+            "Loss after epoch 45900 is 4.4336944\n",
+            "Loss after epoch 45950 is 4.425536\n",
+            "Loss after epoch 46000 is 4.4174347\n",
+            "Loss after epoch 46050 is 4.409361\n",
+            "Loss after epoch 46100 is 4.401283\n",
+            "Loss after epoch 46150 is 4.393225\n",
+            "Loss after epoch 46200 is 4.3851695\n",
+            "Loss after epoch 46250 is 4.3771367\n",
+            "Loss after epoch 46300 is 4.369162\n",
+            "Loss after epoch 46350 is 4.3611794\n",
+            "Loss after epoch 46400 is 4.3532248\n",
+            "Loss after epoch 46450 is 4.34527\n",
+            "Loss after epoch 46500 is 4.3373346\n",
+            "Loss after epoch 46550 is 4.329418\n",
+            "Loss after epoch 46600 is 4.321548\n",
+            "Loss after epoch 46650 is 4.3136845\n",
+            "Loss after epoch 46700 is 4.305833\n",
+            "Loss after epoch 46750 is 4.2979856\n",
+            "Loss after epoch 46800 is 4.290157\n",
+            "Loss after epoch 46850 is 4.282368\n",
+            "Loss after epoch 46900 is 4.2746058\n",
+            "Loss after epoch 46950 is 4.2668395\n",
+            "Loss after epoch 47000 is 4.2591057\n",
+            "Loss after epoch 47050 is 4.2513623\n",
+            "Loss after epoch 47100 is 4.243639\n",
+            "Loss after epoch 47150 is 4.2359667\n",
+            "Loss after epoch 47200 is 4.2283144\n",
+            "Loss after epoch 47250 is 4.2206597\n",
+            "Loss after epoch 47300 is 4.213019\n",
+            "Loss after epoch 47350 is 4.2053847\n",
+            "Loss after epoch 47400 is 4.197782\n",
+            "Loss after epoch 47450 is 4.190225\n",
+            "Loss after epoch 47500 is 4.1826615\n",
+            "Loss after epoch 47550 is 4.175118\n",
+            "Loss after epoch 47600 is 4.167579\n",
+            "Loss after epoch 47650 is 4.160053\n",
+            "Loss after epoch 47700 is 4.1525626\n",
+            "Loss after epoch 47750 is 4.1451054\n",
+            "Loss after epoch 47800 is 4.137654\n",
+            "Loss after epoch 47850 is 4.130212\n",
+            "Loss after epoch 47900 is 4.122782\n",
+            "Loss after epoch 47950 is 4.1153445\n",
+            "Loss after epoch 48000 is 4.107983\n",
+            "Loss after epoch 48050 is 4.100624\n",
+            "Loss after epoch 48100 is 4.093271\n",
+            "Loss after epoch 48150 is 4.0859313\n",
+            "Loss after epoch 48200 is 4.078599\n",
+            "Loss after epoch 48250 is 4.0712757\n",
+            "Loss after epoch 48300 is 4.0640044\n",
+            "Loss after epoch 48350 is 4.056761\n",
+            "Loss after epoch 48400 is 4.0495076\n",
+            "Loss after epoch 48450 is 4.042268\n",
+            "Loss after epoch 48500 is 4.0350304\n",
+            "Loss after epoch 48550 is 4.0278254\n",
+            "Loss after epoch 48600 is 4.020656\n",
+            "Loss after epoch 48650 is 4.0135055\n",
+            "Loss after epoch 48700 is 4.006352\n",
+            "Loss after epoch 48750 is 3.999221\n",
+            "Loss after epoch 48800 is 3.992085\n",
+            "Loss after epoch 48850 is 3.9849706\n",
+            "Loss after epoch 48900 is 3.9779043\n",
+            "Loss after epoch 48950 is 3.9708493\n",
+            "Loss after epoch 49000 is 3.9638073\n",
+            "Loss after epoch 49050 is 3.956756\n",
+            "Loss after epoch 49100 is 3.9497316\n",
+            "Loss after epoch 49150 is 3.9427223\n",
+            "Loss after epoch 49200 is 3.9357584\n",
+            "Loss after epoch 49250 is 3.9288023\n",
+            "Loss after epoch 49300 is 3.9218378\n",
+            "Loss after epoch 49350 is 3.914897\n",
+            "Loss after epoch 49400 is 3.9079638\n",
+            "Loss after epoch 49450 is 3.9010508\n",
+            "Loss after epoch 49500 is 3.8941777\n",
+            "Loss after epoch 49550 is 3.887318\n",
+            "Loss after epoch 49600 is 3.8804762\n",
+            "Loss after epoch 49650 is 3.8736296\n",
+            "Loss after epoch 49700 is 3.86679\n",
+            "Loss after epoch 49750 is 3.859968\n",
+            "Loss after epoch 49800 is 3.8531907\n",
+            "Loss after epoch 49850 is 3.8464336\n",
+            "Loss after epoch 49900 is 3.8396757\n",
+            "Loss after epoch 49950 is 3.8329346\n",
+            "Loss after epoch 50000 is 3.826188\n",
+            "Loss after epoch 50050 is 3.819452\n",
+            "Loss after epoch 50100 is 3.8127787\n",
+            "Loss after epoch 50150 is 3.8061047\n",
+            "Loss after epoch 50200 is 3.7994502\n",
+            "Loss after epoch 50250 is 3.7928014\n",
+            "Loss after epoch 50300 is 3.786149\n",
+            "Loss after epoch 50350 is 3.7795148\n",
+            "Loss after epoch 50400 is 3.772928\n",
+            "Loss after epoch 50450 is 3.7663581\n",
+            "Loss after epoch 50500 is 3.7597787\n",
+            "Loss after epoch 50550 is 3.7532248\n",
+            "Loss after epoch 50600 is 3.7466762\n",
+            "Loss after epoch 50650 is 3.7401314\n",
+            "Loss after epoch 50700 is 3.7336287\n",
+            "Loss after epoch 50750 is 3.7271445\n",
+            "Loss after epoch 50800 is 3.720672\n",
+            "Loss after epoch 50850 is 3.7142055\n",
+            "Loss after epoch 50900 is 3.7077487\n",
+            "Loss after epoch 50950 is 3.7012937\n",
+            "Loss after epoch 51000 is 3.6948748\n",
+            "Loss after epoch 51050 is 3.6884868\n",
+            "Loss after epoch 51100 is 3.6821003\n",
+            "Loss after epoch 51150 is 3.6757364\n",
+            "Loss after epoch 51200 is 3.669365\n",
+            "Loss after epoch 51250 is 3.6630075\n",
+            "Loss after epoch 51300 is 3.6566591\n",
+            "Loss after epoch 51350 is 3.6503675\n",
+            "Loss after epoch 51400 is 3.6440728\n",
+            "Loss after epoch 51450 is 3.6377995\n",
+            "Loss after epoch 51500 is 3.631519\n",
+            "Loss after epoch 51550 is 3.6252565\n",
+            "Loss after epoch 51600 is 3.61899\n",
+            "Loss after epoch 51650 is 3.612775\n",
+            "Loss after epoch 51700 is 3.6065822\n",
+            "Loss after epoch 51750 is 3.60038\n",
+            "Loss after epoch 51800 is 3.5942025\n",
+            "Loss after epoch 51850 is 3.5880246\n",
+            "Loss after epoch 51900 is 3.5818448\n",
+            "Loss after epoch 51950 is 3.5757139\n",
+            "Loss after epoch 52000 is 3.5696058\n",
+            "Loss after epoch 52050 is 3.5635028\n",
+            "Loss after epoch 52100 is 3.5573943\n",
+            "Loss after epoch 52150 is 3.5513074\n",
+            "Loss after epoch 52200 is 3.545228\n",
+            "Loss after epoch 52250 is 3.5391545\n",
+            "Loss after epoch 52300 is 3.53313\n",
+            "Loss after epoch 52350 is 3.527113\n",
+            "Loss after epoch 52400 is 3.5211177\n",
+            "Loss after epoch 52450 is 3.5151153\n",
+            "Loss after epoch 52500 is 3.509117\n",
+            "Loss after epoch 52550 is 3.50313\n",
+            "Loss after epoch 52600 is 3.4971805\n",
+            "Loss after epoch 52650 is 3.4912496\n",
+            "Loss after epoch 52700 is 3.4853241\n",
+            "Loss after epoch 52750 is 3.4794202\n",
+            "Loss after epoch 52800 is 3.473507\n",
+            "Loss after epoch 52850 is 3.467606\n",
+            "Loss after epoch 52900 is 3.4617238\n",
+            "Loss after epoch 52950 is 3.4558768\n",
+            "Loss after epoch 53000 is 3.4500463\n",
+            "Loss after epoch 53050 is 3.4442122\n",
+            "Loss after epoch 53100 is 3.4383948\n",
+            "Loss after epoch 53150 is 3.4325755\n",
+            "Loss after epoch 53200 is 3.4267745\n",
+            "Loss after epoch 53250 is 3.4209945\n",
+            "Loss after epoch 53300 is 3.4152458\n",
+            "Loss after epoch 53350 is 3.4095082\n",
+            "Loss after epoch 53400 is 3.4037755\n",
+            "Loss after epoch 53450 is 3.398037\n",
+            "Loss after epoch 53500 is 3.392319\n",
+            "Loss after epoch 53550 is 3.386605\n",
+            "Loss after epoch 53600 is 3.3809319\n",
+            "Loss after epoch 53650 is 3.3752744\n",
+            "Loss after epoch 53700 is 3.3696232\n",
+            "Loss after epoch 53750 is 3.3639796\n",
+            "Loss after epoch 53800 is 3.358343\n",
+            "Loss after epoch 53850 is 3.3527122\n",
+            "Loss after epoch 53900 is 3.3470953\n",
+            "Loss after epoch 53950 is 3.3415217\n",
+            "Loss after epoch 54000 is 3.335949\n",
+            "Loss after epoch 54050 is 3.3303862\n",
+            "Loss after epoch 54100 is 3.3248417\n",
+            "Loss after epoch 54150 is 3.3192885\n",
+            "Loss after epoch 54200 is 3.3137465\n",
+            "Loss after epoch 54250 is 3.308233\n",
+            "Loss after epoch 54300 is 3.3027437\n",
+            "Loss after epoch 54350 is 3.2972693\n",
+            "Loss after epoch 54400 is 3.291793\n",
+            "Loss after epoch 54450 is 3.2863352\n",
+            "Loss after epoch 54500 is 3.280871\n",
+            "Loss after epoch 54550 is 3.2754228\n",
+            "Loss after epoch 54600 is 3.2700067\n",
+            "Loss after epoch 54650 is 3.2646015\n",
+            "Loss after epoch 54700 is 3.2592132\n",
+            "Loss after epoch 54750 is 3.2538278\n",
+            "Loss after epoch 54800 is 3.24845\n",
+            "Loss after epoch 54850 is 3.243079\n",
+            "Loss after epoch 54900 is 3.2377062\n",
+            "Loss after epoch 54950 is 3.2323837\n",
+            "Loss after epoch 55000 is 3.227075\n",
+            "Loss after epoch 55050 is 3.2217736\n",
+            "Loss after epoch 55100 is 3.2164776\n",
+            "Loss after epoch 55150 is 3.2111833\n",
+            "Loss after epoch 55200 is 3.2059\n",
+            "Loss after epoch 55250 is 3.200622\n",
+            "Loss after epoch 55300 is 3.1953893\n",
+            "Loss after epoch 55350 is 3.190163\n",
+            "Loss after epoch 55400 is 3.1849477\n",
+            "Loss after epoch 55450 is 3.1797345\n",
+            "Loss after epoch 55500 is 3.1745265\n",
+            "Loss after epoch 55550 is 3.169324\n",
+            "Loss after epoch 55600 is 3.1641288\n",
+            "Loss after epoch 55650 is 3.1589909\n",
+            "Loss after epoch 55700 is 3.153848\n",
+            "Loss after epoch 55750 is 3.148711\n",
+            "Loss after epoch 55800 is 3.1435897\n",
+            "Loss after epoch 55850 is 3.1384628\n",
+            "Loss after epoch 55900 is 3.1333463\n",
+            "Loss after epoch 55950 is 3.1282442\n",
+            "Loss after epoch 56000 is 3.1231787\n",
+            "Loss after epoch 56050 is 3.1181252\n",
+            "Loss after epoch 56100 is 3.113071\n",
+            "Loss after epoch 56150 is 3.1080308\n",
+            "Loss after epoch 56200 is 3.1029835\n",
+            "Loss after epoch 56250 is 3.0979574\n",
+            "Loss after epoch 56300 is 3.0929272\n",
+            "Loss after epoch 56350 is 3.0879514\n",
+            "Loss after epoch 56400 is 3.082979\n",
+            "Loss after epoch 56450 is 3.078014\n",
+            "Loss after epoch 56500 is 3.0730433\n",
+            "Loss after epoch 56550 is 3.0680923\n",
+            "Loss after epoch 56600 is 3.0631435\n",
+            "Loss after epoch 56650 is 3.058203\n",
+            "Loss after epoch 56700 is 3.0532978\n",
+            "Loss after epoch 56750 is 3.0484061\n",
+            "Loss after epoch 56800 is 3.0435207\n",
+            "Loss after epoch 56850 is 3.0386405\n",
+            "Loss after epoch 56900 is 3.0337672\n",
+            "Loss after epoch 56950 is 3.0288994\n",
+            "Loss after epoch 57000 is 3.0240276\n",
+            "Loss after epoch 57050 is 3.019199\n",
+            "Loss after epoch 57100 is 3.0143878\n",
+            "Loss after epoch 57150 is 3.0095806\n",
+            "Loss after epoch 57200 is 3.0047886\n",
+            "Loss after epoch 57250 is 2.9999945\n",
+            "Loss after epoch 57300 is 2.9952013\n",
+            "Loss after epoch 57350 is 2.9904191\n",
+            "Loss after epoch 57400 is 2.9856572\n",
+            "Loss after epoch 57450 is 2.980924\n",
+            "Loss after epoch 57500 is 2.9762027\n",
+            "Loss after epoch 57550 is 2.9714816\n",
+            "Loss after epoch 57600 is 2.9667728\n",
+            "Loss after epoch 57650 is 2.9620569\n",
+            "Loss after epoch 57700 is 2.9573514\n",
+            "Loss after epoch 57750 is 2.9526656\n",
+            "Loss after epoch 57800 is 2.9480064\n",
+            "Loss after epoch 57850 is 2.9433608\n",
+            "Loss after epoch 57900 is 2.9387262\n",
+            "Loss after epoch 57950 is 2.9340847\n",
+            "Loss after epoch 58000 is 2.929455\n",
+            "Loss after epoch 58050 is 2.924824\n",
+            "Loss after epoch 58100 is 2.9202101\n",
+            "Loss after epoch 58150 is 2.915625\n",
+            "Loss after epoch 58200 is 2.9110556\n",
+            "Loss after epoch 58250 is 2.906492\n",
+            "Loss after epoch 58300 is 2.9019368\n",
+            "Loss after epoch 58350 is 2.8973753\n",
+            "Loss after epoch 58400 is 2.8928275\n",
+            "Loss after epoch 58450 is 2.8882895\n",
+            "Loss after epoch 58500 is 2.8837662\n",
+            "Loss after epoch 58550 is 2.879273\n",
+            "Loss after epoch 58600 is 2.8747847\n",
+            "Loss after epoch 58650 is 2.8703005\n",
+            "Loss after epoch 58700 is 2.8658257\n",
+            "Loss after epoch 58750 is 2.861356\n",
+            "Loss after epoch 58800 is 2.856888\n",
+            "Loss after epoch 58850 is 2.8524256\n",
+            "Loss after epoch 58900 is 2.848007\n",
+            "Loss after epoch 58950 is 2.8435898\n",
+            "Loss after epoch 59000 is 2.839185\n",
+            "Loss after epoch 59050 is 2.8347774\n",
+            "Loss after epoch 59100 is 2.8303902\n",
+            "Loss after epoch 59150 is 2.8259966\n",
+            "Loss after epoch 59200 is 2.8216062\n",
+            "Loss after epoch 59250 is 2.817236\n",
+            "Loss after epoch 59300 is 2.8129041\n",
+            "Loss after epoch 59350 is 2.8085654\n",
+            "Loss after epoch 59400 is 2.8042452\n",
+            "Loss after epoch 59450 is 2.799919\n",
+            "Loss after epoch 59500 is 2.7956061\n",
+            "Loss after epoch 59550 is 2.791291\n",
+            "Loss after epoch 59600 is 2.78699\n",
+            "Loss after epoch 59650 is 2.7827125\n",
+            "Loss after epoch 59700 is 2.7784588\n",
+            "Loss after epoch 59750 is 2.7741969\n",
+            "Loss after epoch 59800 is 2.7699523\n",
+            "Loss after epoch 59850 is 2.7657125\n",
+            "Loss after epoch 59900 is 2.7614665\n",
+            "Loss after epoch 59950 is 2.7572348\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 2.4361508\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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oZF2Zz7qu5MX6Rb/RhtUvu3Hw9ULz52WMDRrmtiB9ukORzyssT0JbCCGKwY30\n6wzdPpAD1/fjVqUFy7utoaFj4yKdU3U7Gd30KditWYmiVpMx6gPSx08Ee/sinVcUHQltIYQoYjFx\n+xm63ZObGTfo1fh1FnRahN5KX6RzWn+/Bb2fL5ob1zG2eITUsEUY3dsU6Zyi6EloCyFEEVEUhWXH\nP2XKr/4oisL09h8y4tFRRdqOVHXzJvrJfth+uxHF2pr0iVPI8BotLUjLCQltIYQoApnGTMb/PJov\nz3xONbtqLHlxBc/UerboJlQUbL78HP3UiaiTksh5/ElSwxZjatqs6OYUxU5CWwghLOzPlMu8s82T\nYwlHaVO9LUu7rqaWQ+0im0999QoO4z7AetdOFHsdqXOCMQwZJi1Iy6F8hbbBYKB79+6MHDkSDw8P\nJk6ciNFoRKvVEhwcjLOzM5s2bWLlypWo1Wr69OnDm2/e2dEnLi4OPz8/TCYTzs7OBAcHY21tXSQn\nJYQQJWXXlZ2M2PEOSVlJeLYYzIcdgrHR2BTNZGYztss/RT8zEFVGOtmdnic1ZCHmOnWLZj5R4vL1\n17DIyEgqV869ly8sLIw+ffqwZs0aXnjhBZYvX05GRgaLFy9mxYoVrF69mpUrV5KcnHzHGOHh4fTr\n149169ZRr149NmzYYPmzEUKIEqIoCgsPzeft714nPSedBR0jmN8xvMgCW3P2DI49uuIwcTyKjTUp\nER9z+4uNEtjl3AND+8KFC5w/f56OHTsCMG3aNLp27QqAk5MTycnJHD16lFatWuHg4ICtrS1t2rTh\n8OHDd4wTExPD888/D0CnTp3Yt2+fhU9FCCFKRmp2CkO2DWB2zHRq6lzZ9No2BrQYVDST5eRgHxqM\nU+ensfotBkPP17m15zey3uoHxbXftigxDwztoKAg/P398/7b3t4ejUaDyWRi3bp19OjRg4SEBKpU\nqZJ3TJUqVYiPj79jnMzMzLzL4VWrVv3P40IIURadvXWGrhs6sfXSZp6p9Sw73txNmxqPF8lc2qNH\ncHrhOXRzZmJ2qsLtFetI/XQFSvXi2b5TlLz7vqcdFRWFu7s7derUueP7JpMJPz8/2rVrh4eHB5s3\nb77jcUVR7jvpgx7/f05O9mi1mnwdW1DOzg5FOn5FIetYeLKGllGc67jx1EYGRQ0iLTuNcR7jmNNl\nDlp1EXy+NyMDAgNh/nwwm2HYMDTz5lHZ0dHyc/1Nfh4tw9LreN+frujoaK5evUp0dDTXr1/H2toa\nFxcXoqKiqFevHl5eXgBUr16dhISEvOfdvHkTd3f3O8ayt7fHYDBga2vLjRs3qJ6PvxkmJWUU5Jzy\nzdnZgXjZfq7QZB0LT9bQMoq1TT3gAAAgAElEQVRrHU1mE3NiZhJ+ZAH2Wh1LXlhOryZvkJSYafG5\nrH7dg36MN9pLFzHVq0/qgghyOjwHORTZ9pny82gZBV3H+wX9fUM7LCws7+uIiAhq1apFQkICVlZW\n+Pj45D326KOPEhAQQEpKChqNhsOHDzNp0qQ7xmrfvj3bt2+nZ8+e/PDDD3ToIH1vhRBlT2JmIu/t\neIfdf+2iQeWGrOi2DreqLSw+jyrlNroZ07BbtSy3Ben73qRPmCwtSCu4h76Os27dOrKysvD09ASg\nUaNGBAYGMnbsWIYOHYpKpWLUqFE4ODhw6tQpduzYgY+PD97e3kyYMIH169fj6upKr169LH4yQghR\nlP6I/50h2wZwNfUKXeu/xKLnP6GyjeUvUVtv/z63BWlcLEa3lrktSB9ra/F5RNmjUvL7BnMJKOrL\nM3IJyDJkHQtP1tAyinIdvzi9Fr+ffckyZeH35CR82463+Haaqvh49AF+2H7zNYqVFRlj/Mjw9oVi\n7mkhP4+WUeyXx4UQoqLLNmUz5Vd/lh//jMo2jizrtpou9bpadhJFwebrL9EHTEB96xY5bZ8gNXQR\npuZulp1HlHkS2kIIcQ8ms4l3fxjEtktbcKvSkhUvraVB5YYWnUP911X040djs3MHir09abODyHxn\nOGiK9s4ZUTZJaAshxD1M2zuJbZe20KHWc6x6+Qt0VjrLDW42Y7tiKbqZ01Cnp5H9XKfcFqT16ltu\nDlHuSGgLIcRdfPpHJEv+iKR5FTeWdVtt0cDWnD+Hg68XVjH7MFd2JCU8UjqaiXyR0BZCiH/Zdmkr\nAb/4U92+Bmtf+cpynxDPycEuMgJd8BxUWVlk9ehF6ofBKDVqWGZ8Ue5JaAshxD/8fvMwI3a8g53W\njjUvr6eOg2U24ND+8Tv60V5YHf8DU/UapM2dT3b3Vy0ytqg4JLSFEOJvV1Ov0H9LHzKNmax86XPc\nq7cp/KCZmejmB2G3eCEqk4nMfp6kB85CcXQq/NiiwpHQFkIIICXrNv23vEl85k1mPxNEtwYvF3pM\nq/170ft6ob1wHlPd+qTOX0jOc50sUK2oqCS0hRAVXrYpmyHbPTl96xTDW7/PsNbvF2o8VWoKupnT\nsFuxFEWlIuO9UaT7B4DOgp8+FxWShLYQokJTFIXxP49mz1/RdGvwCtPbf1io8ax3bEM/3hdN7DWM\nzZqTGroI4+NPWqhaUdFJaAshKrSwQyF8fnoN7s6PEdnlMzTqgjU1USUkoA+YgO3Gr1CsrEgf50/G\nB2PBxsbCFYuKTEJbCFFhfX32S+YcmEkdh7qsfuXLgt2LrSjYfLMB/WQ/1ImJ5LRpS2roYkxult/5\nSwgJbSFEhbQ/di8f/DSSStaVWfvKV9Swf/h7pdWx19D7+WLzwzYUOzvSZnxI5rD3pQWpKDIS2kKI\nCudC8jkGfd8XM2aWdVtN8yoPuTGH2YztquXoZkxFnZZKdofnSJ0fjrl+g6IpWIi/SWgLISqUhMwE\n+n7Xm6SsJBZ2+ohna3d8qOdrLpxDP8YH632/Yq5UmdSwxRj6DpAWpKJYSGgLISqMTGMmA7e+zeWU\nS4xpO56+bgPy/2SjEbvIReiCP0RlMJD1UnfSguZjdqlZdAUL8S8S2kKICsGsmPHeOYKDNw7wepM3\nmfBkQL6fqzn2R+4GH3/8jtm5OimLl5Ddvae8uhbFTkJbCFEhzN4/nU0XvqFdzfYs7PwRqvwErsGA\n/YJ52EeEojKZMLzdn7Tps1GcqhR9wULchYS2EKLcW3ViORFHQmnk2JiVL63DRvPge6e1+/fhMMYL\n7flzmOrUJTVkITmdni+GaoW4NwltIUS59tOVHUzYPYaqtlVZ98oGnGzv/ypZlZaKblYgdss+zW1B\nOmwE6ROngl5fPAULcR8S2kKIcutEwnHe3T4YrVrLqpe/oEHlhvc93nrnD+jHjUZz7S+MTZvltiB9\n4qliqlaIB5PQFkKUS3FpsfTf8iZpOal89uJKnnC5d/iqEhPRT/HHdsN6FK2W9DF+ZPiOlxakotSR\n0BZClDtp2an039qH2PRrTPGYwauNX7v7gYqCzbcb0U8ajzohgRz3x3JbkLZ8pHgLFiKfJLSFEOWK\n0Wxk+A9DOJ7wBwNbvIOX+wd3PU4dF4t+whhstm3NbUEaOJvM4e+DVn4titJLfjqFEOWGoihM2jOe\nH6/8QOe6XZj7bMh/b+0ym7FdsxLd9CmoU1PIfrpDbgvSho1KpmghHoKEthCi3FiwbwErTiylZdVW\nfPbiSrTqO3/FqS9ewGGsD9a/7sHsUInU+eEYBgySJimizJDQFkKUC5svfMv4HeNx0dVk7Stford2\n+N+DRiN2n3yELmhWbgvSbi+TFrQAc03XkitYiAKQ0BZClHmHbvzGqB+HobPWsfaVr3DV18p7THP8\nWG4L0qNHMFerRmrEx2S9+pq8uhZlkoS2EKJMu3z7Ep5b3yLHnMPGtzbSyrF17gNZWdiHzsM+PBSV\n0YihT1/SZnyIUqVqyRYsRCFIaAshyqxkQxL9t7xJQmYC854N5aUmLxEfn4r2QAwOvqPQnjuLqXYd\nUkPCyOn8QkmXK0ShSWgLIcqkLFMWQ7YN4FzyWUa6+zD4kaGQloZu0njsli4BIHPocNInT0PROzxg\nNCHKBnV+DzQYDHTp0oWNGzcCsGrVKlq2bEl6ejoAx48fx9PTM+8fDw8PDh8+fMcYnp6evPHGG3nH\nHD9+3IKnIoSoKBRFYcwub36N3UP3hj2Z6jEDq59+hEcewf6zTzA1akzypu2kzQmRwBblSr5faUdG\nRlK5cmUAoqKiSExMpHr16nmPP/LII6xevRqAlJQURo4cibu7+3/GmTNnDk2bNi1s3UKICiz4tzl8\ndfYL2tZ4gsg2c6ns/T62X34OWi3pvuPI8PUDW9uSLlMIi8tXaF+4cIHz58/TsWNHALp06YJer2fz\n5s13PX7p0qUMGjQItTrfL+SFECJfvji9lpCDc6nrUI9vzANx7fgs6oR4clq7Y7VyORm1pEmKKL/y\nFdpBQUFMmTKFqKgoAPT32aLOYDDwyy+/8MEHd28dGB4eTlJSEo0aNWLSpEnY3udvw05O9mi1mvyU\nWGDOznLpzBJkHQtP1vDBdl3axdhoH9yyKxOzszEOW71zX1HPm4eVry9otTiXdJHlhPw8Woal1/GB\noR0VFYW7uzt16tTJ14A//vgjHTt2vOur7IEDB9KsWTPq1q3LtGnTWLt2LUOHDr3nWElJGfmas6Cc\nnR2Ij08t0jkqAlnHwpM1fLCzt87Q6+teDDlkZtFOI1ZpO8lu/wxpC8IxNWwMSZmyjhYi62gZBV3H\n+wX9A0M7Ojqaq1evEh0dzfXr17G2tsbFxYX27dvf9fhdu3bRt2/fuz72wgv/u+Wic+fObN269UHT\nCyEENzNu4r+yJxu/SOH5S2DWq0kNDsPgORjkbThRgTwwtMPCwvK+joiIoFatWvcMbMj9FHnz5s3/\n831FURgyZAjh4eFUqlSJmJgYmjRpUsCyhRAVRYYhle1jnmP7pljsjZD1YjfS5oVidq314CcLUc4U\n6D7tyMhI9u7dS3x8PMOGDcPd3R0/Pz8g95Pj/3zPe/fu3fz111/069ePPn36MHjwYOzs7KhRowbe\n3t6WOQshRLmkOvEHhne6M+ZSMikONtwO/ojs13pLC1JRYakURVFKuoh7Ker3VOR9G8uQdSw8WcN/\nycrCPiwE27BgNCYzPzxVnVZL96CtXvO+T5N1tAxZR8soive05c0gIUSpoj14AKcuHdDNDyJWZ2b4\n8No03HDwgYEtREUgbUyFEKVDWhq6uTOx+/RjVIrCR09ASPdqfNX/eyrbOJZ0dUKUChLaQogSZxX9\nEw7jPkBz5U/S69ehV5d4fq2vIqrnV9StVK+kyxOi1JDQFkKUGFVyErppk7H7fA2KRsON94fxZO1N\nXM3JYnmXtTxWo21JlyhEqSLvaQshSoT15m+p8vQT2H2+hpxWj3JtyxY6ue3lSs4NZjz9IS837F7S\nJQpR6khoCyGKlfrGdSoNGUDloZ6oUm6TFjCd+C3b8bw2j1O3TjC01XCGtx5Z0mUKUSrJ5XEhRPFQ\nFGw/X4Nu2mTUt5PJbteetAURGBs1ZkK0D9FXf6Jr/ZeY9XQQKrkPW4i7ktAWQhQ59eVLOIwbjfXu\nXZh1elKDFmAY9A6o1UQcXsCaUytp7exO5AtL0aiLdpMgIcoyCW0hRNExmbD7NBLd3FmoMjLI6vIi\nacFhmGvVBiDq3NfM2h9ILX1t1r78JXqre+8gKISQ0BZCFBHNqZM4jPHC6tBBzFWqkDo/nKzX38xr\nQRoTtx/vn0bgYF2Jda9soIbOpYQrFqL0k9AWQlhWdjb2C+djHxaCKicHw+u9SZs1D6VatbxDLt6+\nwKDv38akmFjadRVuVVuUYMFClB0S2kIIi9EePoiDrxfaUycx1XQlLTiU7BdfuuOYxMxE+n73BrcM\ntwjtuIiOdTqXULVClD0S2kKIwktPRzd3FnafRqIym8kcNJT0KYEolSrfcZjBaGDQ9325dPsio9uM\no3+LgSVUsBBlk4S2EKJQrHZH4zDGB82VyxgbNCQtdBE57Z8BQFEUziWdZV/cr+yP3cu+2F+JTb/G\na43fwP+pgBKuXIiyR0JbCFEgqtvJ6AIDsFu7CkWjIcNrNLfHjudE+nn2HV3E/th9xMTtJdGQmPec\nqrZV6e82kDkdQlCrpLeTEA9LQlsI8dCst2xG7z8WzY3r3G7akNWjOrNRf4wD65qRnpOWd1wtfW3e\naNKHdq7t8aj5NE2cmkrjFCEKQUJbCJFvGX+dRz1+FM4795GtVRH4vIa57S9iTLoISdDEsSntXNvz\nVE0PPFyfpo5D3ZIuWYhyRUJbCHFPCZkJ7I/dS0zsr1SL2sKYDVeokgm/1IHhPcHKrRXv1PSgXc2n\neaqmB872ziVdshDlmoS2ECLP1dQr7I/dy/64veyP3cu55LPUS4JPvoOuFyDdRs2G9zpiGvo+37l6\n4GBdqaRLFqJCkdAWooL69ye7Y+L28Vfa1bzHHTQ6ws80Yfg3l7Ex5JDZqTOGkHCeqyOXvIUoKRLa\nQlQQRrOREwnH/g7p/36yu4ptFV5q0B0P1/Y8n+HK4zMXY33wN8xOTqSEzCXrzbfzWpAKIUqGhLYQ\n5ZTBaOD3m4fZF/sr++P2cuB6zD0/2d2uZnuaOjVDlZODfUQo9qHDUWVnY+j1Ommzg1Gc5b1qIUoD\nCW0hyonU7BR+ux7D/th97Iv7lSM3DpFtzs57vLFjEzxcn77nJ7u1Rw7hMNoL7akTmFxqkha0gOyX\nXinu0xBC3IeEthBlVGp2Cj9fjSYmbi/74vZyPOEPzIoZALVKzSPVWtOupgdP1cy9Bau6ffW7D5SR\ngW7eh9h9vCi3BannYNKnzkCp7FiMZyOEyA8JbSHKmExjJp8d+4SIwwtIzkoGwFptzRMuT9GuZns8\nXNvzhMtT+fpkt9Uvu3EY443m8iVM9RuQuiCCnGeeLepTEEIUkIS2EGWE0Wxk/el1zPvtQ+LSY6ls\n48iYtuN5rk5nHqveFlutbb7HUt1ORjdjKnarV6Co1WSM9CHdbxLY2xfhGQghCktCW4hSTlEUtl76\njg/3T+dc8llsNbb4PDYGr8c+wNHW6aHHs962Fb2fL5rrcRjdWpIatgjjY22LoHIhhKVJaAtRiu29\n9gsz90/j0I3f0Kg0eLYYzLjH/ampd33osVQ3b6Kf7IfttxtRrK1J9w8gw2s0WFsXQeVCiKIgoS1E\nKXQ84Riz9wey88oOALo37MnEp6bQxKnpww+mKNh89QX6Kf6ok5LIefxJUkMXYWrW3MJVCyGKmoS2\nEKXInymXmRszi43nvkJB4WnXDgR4BNK2xhMFGk999QoO40dj/dOPKPY60mYHkfnOcNBoLFy5EKI4\n5Cu0DQYD3bt3Z+TIkbz++uusWrWKoKAgDhw4gE6nA6Bly5a0adMm7zkrVqxA849fDHFxcfj5+WEy\nmXB2diY4OBhruSwnBAA3028yec9UVp5YRo45h5ZVWzHFI5BOdboUbCtLsxnb5Z+inxmIKiOd7I6d\nSQ1ZiLluPcsXL4QoNvkK7cjISCpXrgxAVFQUiYmJVK9+5z2fer2e1atX33OM8PBw+vXrx0svvcSC\nBQvYsGED/fr1K0TpQpR9admpRB5dROTRCNKy06hbqT4TnwzgtSa9UavUBRpTc+4sDr5eWB3Yj9nR\nkdS5kWS91U9akApRDjzwt8KFCxc4f/48HTt2BKBLly74+vo+9N/+Y2JieP755wHo1KkT+/bte/hq\nhSgnsk3ZfPbHxzy59lGCf5uDvZU9czoEs7fvQd5o2qdggZ2Tg31YCE6d2mN1YD+GV1/j1p7fyHq7\nvwS2EOXEA19pBwUFMWXKFKKiooDcV9R3k52dzdixY7l27Rpdu3ZlyJAhdzyemZmZdzm8atWqxMfH\nF7Z2Icocs2Jm47mvmHtgNldSLqOz0uP3xCQCnvfHkFLwcbVHj+S2ID1xDFP1GrktSF/pYbnChRCl\nwn1DOyoqCnd3d+rUqfPAgfz8/Hj11VdRqVQMGDCAxx9/nFatWt31WEVR8lWck5M9Wm3RfmDG2dmh\nSMevKGQd709RFLZf2I7/j/4cvXEUK7UVPk/6MPnZyVTX5b7V5FCQPTkyMyEwEObPB5MJhg5FExxM\nZaeHv3+7vJCfRcuQdbQMS6/jfUM7Ojqaq1evEh0dzfXr17G2tsbFxYX27dv/59i+ffvmfd2uXTvO\nnj17R2jb29tjMBiwtbXlxo0b/3lP/G6SkjIe5lwemrOzA/HxqUU6R0Ug63h/h278xqx9gfwauwcV\nKno3fYsJT06mXqX6kAHxGakFWkOrvb+g9/VCe+kipnr1SZ0fTs6zHcEIVNA/D/lZtAxZR8so6Dre\nL+jvG9phYWF5X0dERFCrVq27BvbFixdZvHgxISEhmEwmDh8+TLdu3e44pn379mzfvp2ePXvyww8/\n0KFDh4c9DyHKlHNJZ/kwZgZbLm4CoEvdF5ncLpCW1R4p1LiqlNvoZkzDbtWy3BakI7xInzAZ/r6T\nQwhRfj30fdqRkZHs3buX+Ph4hg0bhru7O35+fri4uNC7d2/UajWdO3emdevWnDp1ih07duDj44O3\ntzcTJkxg/fr1uLq60qtXr6I4HyFKXFxaLMG/zeHz02swKSba1niCqR4z8HB9utBjW2//PrcFaVws\nxuZupIYuwti2YPdwCyHKHpWS3zeYS0BRX56RS0CWIeuYK9mQRMSRMD79IxKDyUBTp2ZMemoaLzV4\n5YF3WzxoDVUJCegD/LDduAHFyooM3/Fk+IyRFqT/Ij+LliHraBnFfnlcCPFg/79VZvjhBdzOSqam\nzpUJT06mT7O+aNWF/F9MUbD5+kv0ARNQ37pFTtvHSQ1djKm5m2WKF0KUKRLaQhSQ0Wzki9NrCf5t\nDnHpsTjaODLVYyZDWw3HTmtX6PHV1/5CP340Nj/+gGJvT9rMOWS+O0JakApRgUloC/GQFEVhy8XN\nzImZwbnks9hp7fB5bAzebUZT2cax8BOYzdiuWIpu5jTU6WlkP9uJ1PkLMderX/ixhRBlmoS2EA/h\n12t7mLV/GoduHPx7q8whjH/CHxddTYuMrzl/Dv0Yb6z378Vc2ZGUhR9JRzMhRB4JbSHy4XjCMWbt\nn8ZPV34EcrfKnPTUVBo7NbHMBDk52IUvQBc8B1VWFlmvvEra3BDMNVwsM74QolyQ0BbiPv69VeYz\ntZ4loF0gbWo8brE5tMeOwlhv9L//jtm5Oilz55Pdo6fFxhdClB8S2kLcRXxGPKGH5uVtlflItdYE\ntAukU53nC7ZV5t1kZqKbH4Td4oVgMpHZdwDp02ejOFbcFqRCiPuT0BbiH9KyU/no9wgijy4iPSeN\nepXqM/GpKfRq/EaBt8q8G6v9e3NbkF44j6luPTSffUqaezuLjS+EKJ8ktIUgd6vMVSeWseDQPBIy\nE6hm50xAu2l4thiCtcZyDUxUqSnoZk7DbsVSFJWKjPdGkj4hAOcGNStsv3AhRP5JaIsKL9OYSa+o\nlzhy83DeVpkj3L3QW919G9qCsv5xO/pxo9HEXsPYrHluC9LHn7ToHEKI8k1CW1R4E3eP48jNw/Ro\n1IugZxdQza6aRcdXJSaiD5iA7ddfomi1pI+dQMbocWBjY9F5hBDln4S2qNDWnlzFutOrae3szuLn\nl2CrtbXc4IqCzTcb0E/2Q52YSM5jbXJbkLZoabk5hBAVioS2qLCOxR/Ff89YHG0cWdp1lUUDWx17\nDb2fLzY/bEOxsyNt+odkDn9fWpAKIQpFQltUSMmGJIZs9yTLlMXybmuoV6m+ZQY2m7FdtRzdjKmo\n01LJ7vAcqSELMTdoaJnxhRAVmoS2qHDMihmvne9xJeUyY9qOp0u9rhYZV3PxPHpfb6z3/Yq5UmVS\nQxdh6OcpLUiFEBYjoS0qnPDDC/jhz208W7sT45+YVPgBjUbsIhehC/4QlcFA1kvdSQuaj9nFMv3I\nhRDi/0loiwpl91/RzD0wC1ddLT5+YSkadeHeY9Yc+wMHXy+s/vgdczVnUhYvIbt7T3l1LYQoEhLa\nosKITbvGiB3voFFp+KzrysLd2mUwYL9gHvYRoahMJgxv9SNtxocoTlUsV7AQQvyLhLaoELJN2by7\nfRAJmQnM6RDC4y4Fb2qijdmPg+8otOfPYapTl9TgMHI6d7FgtUIIcXcS2qJCmL43gIM3DvB6k968\n88iwAo2hSktFN3s6tss+BSBj2AjSJ04FvWU7pwkhxL1IaIty75tzG/j02Mc0c2pOSMfwAu3SZfXT\nDhzGjUbz11WMTZqSGroY45NPFUG1QghxbxLaolw7e+sMvru80VnpWdZtzUP3E1fdSkQ/ZSK2X32R\n24J0jB8ZvuOlBakQokRIaItyKy07lSHb+pNhTOezF1fSxKlp/p+sKNhs+gb9xHGoExLIcX8stwVp\ny0eKrmAhhHgACW1RLimKwphob84ln+W9R0fxauPX8v1cdVws+gljsNm2FcXWlrRps8h8byRo5X8X\nIUTJkt9Colz67NjHRJ3fyJMu7Zjabkb+nqQo2K5ZiS4wAHVqCtlPdyB1fjjmho2KtlghhMgnCW1R\n7hyIi2Ha3slUs3Pm0xdXYKWxeuBz1Jcu4jDWB+tfdmN2qETq/HAM/QeCWl0MFQshRP5IaItyJT4j\nnmE/DMKsmFny4nJq6l3v/wSjEbtPPkI3bzaqzEyyur1MWtACzDUf8DwhhCgBEtqi3DCZTYzY8Q5x\n6bEEtJvOM7Weve/xmhPHcfAdhdXvRzBXq0bqwo/I6vm6tCAVQpRaEtqi3Ag6MJs9136mW4NX8H5s\n9L0PzMrCPjQY+/AFqIxGDG++TdrMOShVqhZfsUIIUQAS2qJc2H75e8IOh1C/UgMiOkfes4GK9kAM\nDmO80J49g6l2HVJDwsjp/EIxVyuEEAWTr0/ZGAwGunTpwsaNGwFYtWoVLVu2JD09Pe+YrVu30rt3\nb/r06UNoaOh/xvD396dHjx54enri6elJdHS0Zc5AVHiXb19i1I/DsdXYsrTbairbOP73oLQ0dJP9\ncOzxItqzZ8gcOpyk3fslsIUQZUq+XmlHRkZSuXJlAKKiokhMTKR69ep5j2dmZhISEsKmTZvQ6XT0\n6dOHHj160Lhx4zvGGTNmDJ06dbJg+aKiyzRmMnT7QFKybxPeOZJW1Vr/5xirXTtxGPcBmqtXMDZu\nQuqCRRjbeZRAtUIIUTgPDO0LFy5w/vx5OnbsCECXLl3Q6/Vs3rw57xg7Ozs2bdqE/u+NExwdHUlO\nTi6aioX4h0l7xnMs4SieLQbzdvP+dzymSrqFfuokbNevQ9FoSPcdR4avH9jallC1QghROA+8PB4U\nFIS/v3/ef+vvsaPR/3//zJkzXLt2jUcfffQ/x6xZs4aBAwfi6+vLrVu3ClqzEACsPbmKtadW0drZ\nndnPzPvfA4qC9eYoqjz9BLbr15HT2p2kH34mY+JUCWwhRJl231faUVFRuLu7U6dOnXwNdvnyZcaN\nG8f8+fOxsrqzoUXPnj1xdHTEzc2NJUuWsGjRIqZOnXrf8Zyc7NFqNfmau6CcnR2KdPyKorjX8Ujc\nEfz3jMXJ1omovhup4+Sc+0BsLIwaBVFRuQEdFITVmDFUKQMtSOVn0TJkHS1D1tEyLL2O9/1NFh0d\nzdWrV4mOjub69etYW1vj4uJC+/bt/3Ps9evXGTVqFPPmzcPNze0/j3t4/O89xM6dOxMYGPjA4pKS\nMvJxCgXn7OxAfHxqkc5RERT3OiYbkui14XWyTFks67oavbEa8TdTsF23Gt20yahTbpPt8TRpoRGY\nGjaGpMxiq62g5GfRMmQdLUPW0TIKuo73C/r7hnZYWFje1xEREdSqVeuugQ0wefJkAgMDadmy5V0f\n9/b2xs/Pjzp16hATE0OTJk3yU7sQdzArZrx/GsGVlMuMaTueF+p3Q335Um4L0j0/Y9Y7kBochsFz\nsLQgFUKUOw99zTAyMpK9e/cSHx/PsGHDcHd358033+TgwYOEh4fnHTd48GBcXV3ZsWMHPj4+9O/f\nn9GjR2NnZ4e9vT1z5syx6ImIiiHicCjbL3/Ps7U7Mb7NBOwiF6GbOzO3BemL3UibF4rZtVZJlymE\nEEVCpSiKUtJF3EtRX56RS0CWUVzruPuvaPps7oWLfU32PPoZdfwDsDp8CHPVqqR9GExWrzfKbAtS\n+Vm0DFlHy5B1tIxivzwuRGkRlxbLiB3vYGdSE32hMw0mvYoqJwfDG31ImxWEUlVakAohyj8JbVHq\nZZuyGbp9II3OJrD5xxo4/7kak2st0oJDyX6hW0mXJ4QQxUZCW5R6c3f502/lAT6IAbVyg8wh75Ie\nEIjiUKmkSxNCiGIloS1KtQPrZjAm8DMaJENOg4akhC0mx+Ppki5LCCFKhIS2KJVUyUmY/L14ZeNm\njGr4a/hgbCYHgZ1dSYbCcLYAABh3SURBVJcmhBAlRkJblDrW321C5z8G7c2bHHGBP+dM5+lXfEu6\nLCGEKHES2qLUUN24gcPEcdh89y3ZVur/a+/O46Iq9z+Af2bYhxlBEK57dkvFnfRaaWHgFrj8LCUE\nVDTXUkhwo7iampkCioqalmku2WpFdsOrllJ5Nb2KeTERxNxS2QScGWaGZeb5/UFNkShDDswMfN7/\nyHCec/ie70v5eOY85xm8PAhQzpiBpf4MbCIigKFN1kAIOH24G/JX4yC9XYJr3TtgsP9luHd/HJ/7\nvWHp6oiIrAZDmyxKeuUyFHNnw/G7wzC4ynE2Lgq9Hd+Em4sXPhm6HQ52DrUfhIioieDizGQZej1c\n3n4THk89DsfvDqNs0BDkHNiHoc0/hV4i8PbQd9FK3trSVRIRWRVeaVODszufCUXMLDicOgmDhwdU\nq9ZB8+wYTP1qNG6W3sDCx5fgyTYDLF0mEZHVYWhTwykvhyw5CbI1iVVLkD47BurXEyC8vJBw/DV8\n/0saAjsMQ+Qj0ZaulIjIKjG0qUHYp5+EIiYS9pnnoG/VGuqENSh/OggAcODyPqw5tQoPNOuA9YM2\nQyrhXRsiopowtKl+lZbCNX45XN5+ExKDAdqIySh9dSlEMzcAwOXblzDrmxlwtnPGtsD34ObkbuGC\niYisF0Ob6o3D999CMScKdlcuo/LBv0O9ZgMq+j9p3K6t1GLK/gjcLitB8sBN6NGipwWrJSKyfgxt\nMjvJ7RK4LlkIl907IaRSaCKjUTr/lTuWII37fj4yCs9gfJeJCPUZZ6FqiYhsB0ObzMox9V+Qx86B\nXV4uKrt2h2rtBlT69r5j3PuZu7A7cyd6evniDb9EC1RKRGR7GNpkFpL8fMjj5sN57+cQjo4ofWUR\nNJHRgMOdi6NkFJzBy9/NhZuTO7Y+vRPO9s4WqJiIyPYwtOn+CAHs2AGP6GhIS0pQ0fcxqNZuhL5j\npxqHl+iKMXn/BOj0Omx9eiceaNahYeslIrJhDG36y6RXr0AxbzaQdggSmStUKxKhe34aIK35kS2D\nMCDq0Au4oryMOX3mY0iHwAaumIjItjG0qe70eji/uwXy15dCoikFAgNRtHwVDO3a33O39elrsP/y\nPgxoG4D5feMaqFgiosaDq1hQndhlnYf7yKehiFsA4eQI5Ya3gNTUWgP7+1++xYoTy9DatQ02D9kK\nO6ldA1VMRNR48EqbTFNeDtmGtZAlJUBSXg7dqNFQL0+A8PYGJJJ77npTfQMzDj4PO4kd3nl6B1q4\ntGigoomIGheGNtXK/sd0KKIjYX/uLPQtW0Edn4TyoOEm7VuuL8eU/REo1BZihV8i/tHy0Xquloio\n8WJo091pNHBNeAMumzdULUE6YRJKX30Nws30pUZfO7YIJ/NOYHTHYEzuPr0eiyUiavwY2lQjhyPf\nVS1BevkS9A90gCppPSr8nqrTMVIufIq3/7cJnZp3xir/ZEhqeRudiIjujRPRqBqJ8jbkc2fDffQI\nSK9egebFKBR9+0OdAzu7KAsxaVFwdZDj3cDdkDvI66liIqKmg1faZOT471TIF8TALvcmKrt0q1qC\n9JE+dT6OukKNyfvHo7RCjS1Dt6Nj85oXWiEiorphaBMkBQWQ/3M+nFM+g3BwQGnsP6GJigEcHU3a\nXwiBm+obyCw6h8xb57D/ciqyi7Mwo+dMjHp4dD1XT0TUdDC0mzIh4PTJh5AvehnS4mJU9OlbtQRp\nZ5+77nK7rASZRZk4f+scMot+Quatc8gqzkSxrrjaOL+2/ni137L6PgMioibFpNDW6XQYMWIEZs6c\nidGjR2Pnzp2Ij4/HiRMn4OrqCgDYu3cvduzYAalUipCQEDz33HPVjnHz5k0sWLAAer0eXl5eSExM\nhKOJV3JkftJfrkExbzYcD30NIZNBvTwe2snTAbuqRU/K9GXILs76NZzPIfPWTzhflInr6l+qH0ci\nxcMeD+OJ1gPg49EFXTy7oatnVzzo9hCkEk6ZICIyJ5NCe9OmTXBzcwMApKSk4NatW/D29jZu12g0\n2LhxI/bs2QMHBwcEBwdjyJAhcHf//dGg5ORkhIeHIygoCElJSdizZw/Cw8PNfDpUK4MBzu++A9fX\nl0BaqkbZUwE4t2QezriU4PzpVci8dQ7ni87hYkkO9EJfbdeWrq0Q0G4QfDy6ootnV3T17IaOzTuj\nfStvFBSoLHM+RERNSK2hffHiReTk5MDf3x8AMHjwYMjlcnz55ZfGMWfOnEGPHj2gUCgAAL1790Z6\nejoGDhxoHHP8+HEsXboUABAQEIBt27YxtBuQEAIlGcfgMTcGijOZULs6ImFCe6zu9AM031ZfKEXh\n2Ax9/tYXXTy7wcejC7r++mdzZw8LVU9ERIAJoR0fH49FixYhJSUFACCX3/noTmFhITw8fv+F7uHh\ngYKCgmpjtFqt8e1wT0/PO7aT+ajLVcgsOofzRZnIvPUTsvPOYsgX6Zj/tRZOeuCTrkBUUDmK3XLR\n0b0zunh2hY9HV3T17IouHt3QWt6Gz1QTEVmhe4Z2SkoKfH190a5duzodVAhxX9t/07y5DPb29fvB\nEl5eino9fn0q15cjqzALGfkZOJt/Fhn5GcjIy8CV21eMY3rfALZ+AfjmAUXuTvg0ZiTsxzyHw949\n8LDHw3CwczBLLbbcR2vBHpoH+2ge7KN5mLuP9wzttLQ0XLt2DWlpacjNzYWjoyNatmyJ/v37Vxvn\n7e2NwsJC4+v8/Hz4+vpWGyOTyaDT6eDs7Iy8vLxq98TvprhYU5dzqTMvL4VN3Is1CAOuqa4a7zdn\n3voJmUXnkFNyAZWGympjvVy8MaBtAHrKO2HiFz+j98ffQKo3QDsuAobFyzDEvblxbEmRDoDuvuuz\nlT5aM/bQPNhH82AfzeOv9vFeQX/P0F67dq3x6/Xr16NNmzZ3BDYA9OrVCwsXLoRSqYSdnR3S09MR\nF1f985L79++P/fv3Y9SoUThw4AD8/Pzqeh5NTp4mD3MPR+E/N46gtEJdbZurgxy9vB4x3m+uuv/c\nFS1cWsDh6BHI50TB/ueL0LfvgJLV61DxVICFzoKIiMylzs9pb9q0CUePHkVBQQGmTZsGX19fLFiw\nAHPnzsWUKVMgkUgwa9YsKBQKZGZm4uDBg3jppZcQFRWF2NhYfPTRR2jdujWeeeaZ+jifRiOj4Awi\n9oXhuvoXdHTvhB5ePX+dtd0NXTy6oq2i3R2PVElUSrjOj4HLjq0QUik0L0SiNPafwK+P5RERkW2T\nCFNvMFtAfb89Y61vAf3r4l5EfjMd2kot/vn4EkQ9El3rxDDHA/sgnx8Du5s3UOnTBao1G1DZp2+D\n1GutfbQl7KF5sI/mwT6aR4O/PU4NSwiBtadWYcWJZZDZu2J70PsIevDen1stKSyEfOECOH+2p2oJ\n0vmvQDN7rslLkBIRke1gaFsJbaUWMYcj8dmFT9BW3g67hn2Ebi26330HIeD06ceQL4yFtKgIFX3+\nAdWajdD7dGm4oomIqEExtK1AniYPk/aF4VTeSfRt+RjeDdwNb9ndZ9dLr/8C+fxoOH19oGoJ0mUr\noJ36gnEJUiIiapwY2haWUXAGE1JDcaP0OkI6h2G1fzKc7JxqHmwwwHnHNrguWwypWoVyP3+oVq+D\nocODDVs0ERFZBEPbgv444WxRv9cQ6Tv7rhPO7C5egDwmCo4/HIXBzR3KdW+iLHQcwJXLiIiaDIa2\nBfx5wtmOoA8Q+OCwmgdXVMBl03q4Jq6ApKwMZcNGQh2/Goa/tWzYoomIyOIY2g2sasLZLHx2YU+t\nE87sM85AHh0Jh4wzMHh5Q7lyNcpHjmrgiomIyFowtBtQXmkuJu4LQ3r+KfRt+Ri2B74PL5nXnQN1\nOriujofLhrWQ6PXQhY6DeulyiOb8lC0ioqaMod1A/lfwIyJSw2qdcObww1HIYyJhfzEH+vYPQJW4\nFhUBgyxQMRERWRuGdgP48uIXiPxmOnSVurtOOJOolHB9fQlc3n0HQiKBZvqLKH15EVDDR6ESEVHT\nxNCuR0IIrDmViJUnXoerg/yuE84cv95ftQTp9V9Q2dkHqqT1qOz7mAUqJiIia8bQrid/nHDWTtEe\nO4M+vGPCmeTWLcgXxsL5048h7O1ROjcWmuh5gNNdntMmIqImjaFdD/JKcxGxLxSn89PxaMvH8W7g\n7uoTzoSAU8qnkMfNh/TWLVQ80huqpA3Qd7vHsqVERNTkMbTN7H8FP2JCaihult7A2M7hWOW/rtqE\nM+mN65DHzoHT/n0QLi5QL30D2ukvcglSIiKqFUPbjP444ezVfsswy/el3yecGQxw3rUdrq+9CqlK\nifInB0C1OhmGB/9u2aKJiMhmMLTNQAiBpFMJiD+xHK4Ocuwc9iGe7hBk3G73cw7kc16C49EjMDRz\ngyppPXTjIrgEKRER1QlD+z5pK7WIPjQTn+d8inaK9tg17CN09exWtbGyEi6bN8I1YTkkOh3KAodD\nnZAEQ8tWli2aiIhsEkP7PuSW3sTEfWE1TjizO5sBRUwkHM6chqGFF5Qb3kL5yGd4dU1ERH8ZQ/sv\n+uOEs1CfcUh8am3VhDOdDrI1CZCtXwtJZSV0IWFQv/YGhIenpUsmIiIbx9D+C768mILIb2bcMeHM\n/vgPUMyJhP2FbOjbtoNq1TpUDBxs6XKJiKiRYGjXgRACq0/GI+G/b1SbcCZRq+C6fCmct20BAGim\nzoAm7lUIucLCFRMRUWPC0DaRtlKL2YdeRErOZ2iveAA7h32Irp7d4HDoIBTzomH3yzVUduwE1ZqN\nqHyUS5ASEZH5MbRNkFt6ExGpofix4LRxwpm3Tgp55Aw4f/xB1RKkc+ZDEz0fcHa2dLlERNRIMbRr\ncSb/NCbsC0Vu6c2qCWcD1qDZV6mQvzIf0sICVPR6BKo1G6Dv3sPSpRIRUSPH0L6HvTmfI+rQC9BV\n6rC43+uIbBkMxeTn4fTvryCcnaFe/Dq0M2YC9mwjERHVP6ZNDYQQWHVyJRL/uwKuDnLsCvoA//ef\nArg+9xikytso7/8kVEnrYfj7Q5YulYiImhCG9p9oKjSYfWgmvrhYNeHsk26r4Dt3PRyPfAeDohlU\nq9ZBN34iIJVaulQiImpiGNp/cFN9AxP3heHHgtPo7/04Prs+EN7PRkCi1aLs6SCoE9bA0Kq1pcsk\nIqImiqH9qx/z0xGxLwy5pTexQDYcy96+Accf34ChRQuo1r2JslGjuQQpERFZFEMbwBc5n+GlQy/C\noNMi7VIABny0v2oJ0uCxUC9bCeHJJUiJiMjymnRoCyGQcOINrDq5EgE3XfD5gTZwu3QY+jZtoV61\nFuWDhlq6RCIiIiOTQ1un02HEiBGYOXMm+vXrhwULFkCv18PLywuJiYnIzs5GfHy8cXxOTg42btyI\n3r17G783YcIEaDQayGQyAEBsbCy6d+9uxtMxnaZCg9BPp+Kr9I/xzhEFJh9RQyKuQzt5GkoXLuES\npEREZHVMDu1NmzbBzc0NAJCcnIzw8HAEBQUhKSkJe/bsQXh4OHbt2gUAUCqVmDlzJnx9fe84zooV\nK9CpUyczlf/X3FTfQMS+MHgfO40L+5zQ6pYKlQ93hCppAyof72fR2oiIiO7GpOeWLl68iJycHPj7\n+wMAjh8/jkGDBgEAAgICcOzYsWrjt27diokTJ0JqhY9F/ZifjpCdAzB7y2kceA9oWVKJ0uh5KD70\nHwY2ERFZNZOutOPj47Fo0SKkpKQAALRaLRwdHQEAnp6eKCgoMI7V6XQ4cuQIZs+eXeOxkpOTUVxc\njIceeghxcXFwvsda3c2by2Bvb2fyydTm458+xufLxyNtbwValgLikUcg2bYNrr6+cDXbT2mavLx4\nO+F+sYfmwT6aB/toHubuY62hnZKSAl9fX7Rr167G7UKIaq+//vpr+Pv713iVHRERgc6dO6N9+/ZY\nvHgxdu/ejSlTptz1ZxcXa2orz2TqMiX0YaH4IEOg0skB6oULIV8ch4JiLVCgMtvPaYq8vBQoYA/v\nC3toHuyjebCP5vFX+3ivoK81tNPS0nDt2jWkpaUhNzcXjo6OkMlk0Ol0cHZ2Rl5eHry9vY3jDx8+\njLCwsBqPNWTIEOPXAwcORGpqal3O477I9fZ49rIMykd9ULnubegf6gg51wwnIiIbUmtqrV271vj1\n+vXr0aZNG5w+fRr79+/HqFGjcODAAfj5+RnHnD17Fj4+PnccRwiB559/HsnJyWjWrBmOHz+Ojh07\nmuk0TCCTQZV1jR/uQURENusvzRSLiopCSkoKwsPDUVJSgmeeeca4TalUQi6XG19/9913eP/99yGR\nSBASEoJJkyZh3LhxyM3Nxbhx4+7/DOqCgU1ERDZMIv58U9qK1Pc9Fd63MQ/28f6xh+bBPpoH+2ge\n9XFP2/qeySIiIqIaMbSJiIhsBEObiIjIRjC0iYiIbARDm4iIyEYwtImIiGwEQ5uIiMhGMLSJiIhs\nBEObiIjIRjC0iYiIbIRVL2NKREREv+OVNhERkY1gaBMREdkIhjYREZGNYGgTERHZCIY2ERGRjWBo\nExER2Qh7SxdQ3xISEnDq1ClUVlZixowZGDp0KADg+++/x9SpU5GVlQUAOH/+POLi4gAAgwYNwqxZ\nsyxWszUytY9r1qzB8ePHIYTA4MGDMW3aNEuWbXX+3MdDhw7hp59+gru7OwBgypQp8Pf3x969e7Fj\nxw5IpVKEhITgueees3Dl1sPUHqampmLbtm2QSqXo168fYmJiLFy5dTG1j7+ZM2cOHB0dsXLlSgtV\nbJ1M7aPZMkY0YseOHRNTp04VQghRVFQknnrqKSGEEDqdTowfP1488cQTxrHBwcHi7NmzQq/Xi5iY\nGKHRaCxRslUytY9ZWVli7NixQggh9Hq9CAwMFPn5+Rap2RrV1MfY2Fhx6NChauNKS0vF0KFDhVKp\nFFqtVgwfPlwUFxdbomSrY2oPNRqNCAgIECqVShgMBhEcHCwuXLhgiZKtkql9/M2RI0fEmDFjRGxs\nbEOWafXq0kdzZUyjvtLu27cvevbsCQBo1qwZtFot9Ho9Nm/ejPDwcCQmJgIACgsLodFo0K1bNwBA\nUlKSxWq2Rqb2UaFQoKysDOXl5dDr9ZBKpXBxcbFk6Vblbn38szNnzqBHjx5QKBQAgN69eyM9PR0D\nBw5s0Hqtkak9dHFxwd69eyGXywEA7u7uKCkpadBarZmpfQSA8vJybNq0CS+++CIOHjzYkGVaPVP7\naM6MadT3tO3s7CCTyQAAe/bswYABA3D16lWcP38eQUFBxnHXr1+Hm5sbXn75ZYSGhmL79u0Wqtg6\nmdrHVq1aITAwEAEBAQgICEBoaKjxlybV3Ec7Ozu89957iIiIQExMDIqKilBYWAgPDw/jfh4eHigo\nKLBU2VbF1B4CMP7dy8rKwvXr19GrVy+L1W1t6tLHt956C2FhYfy3XANT+2jWjLmv9wZsxMGDB0Vw\ncLBQKpVi2rRp4sqVK0IIIQICAoQQQpw+fVr4+fmJoqIiodFoxMiRI0V2drYlS7ZKtfXx6tWrYsyY\nMUKj0QilUimGDRsmCgsLLVmyVfpjH48ePSrOnTsnhBDirbfeEkuXLhV79+4Vy5cvN45PSkoSH374\noaXKtUq19fA3ly5dEiNGjDBup+pq6+OlS5fE9OnThRBC/PDDD3x7/C5q66M5M6ZRX2kDVROlNm/e\njC1btkCj0eDnn3/GvHnzEBISgvz8fIwfPx6enp7o2LEjmjdvDhcXF/Tp0wcXLlywdOlWxZQ+ZmRk\noFevXnBxcYFCoUDnzp2RnZ1t6dKtyh/7qFAo0K9fP3Tp0gUAMHDgQGRnZ8Pb2xuFhYXGffLz8+Ht\n7W2pkq2OKT0EgNzcXMyaNQsrV640bqffmdLHtLQ03LhxAyEhIVi6dCnS0tKwZcsWC1duXUzpo1kz\nxpz/27A2SqVSjBgx4q5Xe79dIQohxNixY0VxcbHQ6/Vi7NixIjMzs6HKtHqm9jEjI0OEhIQIvV4v\nysvLxfDhw8W1a9caslSrVlMfIyMjxdWrV4UQQrz33ntiyZIlQqvVisGDB4vbt28LtVptnJRGpvdQ\nCCEmT54sTpw4YZE6rV1d+vgbXmnfqS59NFfGNOqJaKmpqSguLkZ0dLTxe/Hx8WjduvUdY1955RVM\nmzYNEokEfn5+8PHxachSrZqpfezevTueeOIJhIeHAwCCg4PRtm3bBq3VmtXUx9GjRyM6OhouLi6Q\nyWRYsWIFnJ2dMXfuXEyZMgUSiQSzZs0yTkpr6kzt4aVLl3Dy5EkkJycbx02aNAmDBg2yRNlWx9Q+\n0r3VpY/myhh+NCcREZGNaPT3tImIiBoLhjYREZGNYGgTERHZCIY2ERGRjWBoExER2QiGNhERkY1g\naBMREdkIhjYREZGN+H+iZ986rtIL9AAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe5810b7e48>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "jx1IGDdavOIZ",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 22221
+        },
+        "outputId": "ce0febe6-790b-4f77-f819-ad5945638d98"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=65000,interval=50)"
+      ],
+      "execution_count": 33,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Loss after epoch 35000 is 6.7498674\n",
+            "Loss after epoch 35050 is 6.736341\n",
+            "Loss after epoch 35100 is 6.7228174\n",
+            "Loss after epoch 35150 is 6.7093277\n",
+            "Loss after epoch 35200 is 6.6958494\n",
+            "Loss after epoch 35250 is 6.6824474\n",
+            "Loss after epoch 35300 is 6.669072\n",
+            "Loss after epoch 35350 is 6.6557093\n",
+            "Loss after epoch 35400 is 6.6423593\n",
+            "Loss after epoch 35450 is 6.629055\n",
+            "Loss after epoch 35500 is 6.6158056\n",
+            "Loss after epoch 35550 is 6.602567\n",
+            "Loss after epoch 35600 is 6.589341\n",
+            "Loss after epoch 35650 is 6.576157\n",
+            "Loss after epoch 35700 is 6.56305\n",
+            "Loss after epoch 35750 is 6.54993\n",
+            "Loss after epoch 35800 is 6.536834\n",
+            "Loss after epoch 35850 is 6.5237727\n",
+            "Loss after epoch 35900 is 6.510758\n",
+            "Loss after epoch 35950 is 6.497785\n",
+            "Loss after epoch 36000 is 6.484812\n",
+            "Loss after epoch 36050 is 6.471871\n",
+            "Loss after epoch 36100 is 6.458971\n",
+            "Loss after epoch 36150 is 6.446119\n",
+            "Loss after epoch 36200 is 6.4332905\n",
+            "Loss after epoch 36250 is 6.420462\n",
+            "Loss after epoch 36300 is 6.4076543\n",
+            "Loss after epoch 36350 is 6.39493\n",
+            "Loss after epoch 36400 is 6.382219\n",
+            "Loss after epoch 36450 is 6.369523\n",
+            "Loss after epoch 36500 is 6.3568425\n",
+            "Loss after epoch 36550 is 6.3442206\n",
+            "Loss after epoch 36600 is 6.3316355\n",
+            "Loss after epoch 36650 is 6.319064\n",
+            "Loss after epoch 36700 is 6.306503\n",
+            "Loss after epoch 36750 is 6.2939878\n",
+            "Loss after epoch 36800 is 6.281519\n",
+            "Loss after epoch 36850 is 6.2690606\n",
+            "Loss after epoch 36900 is 6.25664\n",
+            "Loss after epoch 36950 is 6.2442183\n",
+            "Loss after epoch 37000 is 6.231861\n",
+            "Loss after epoch 37050 is 6.219538\n",
+            "Loss after epoch 37100 is 6.207241\n",
+            "Loss after epoch 37150 is 6.194936\n",
+            "Loss after epoch 37200 is 6.1826687\n",
+            "Loss after epoch 37250 is 6.170473\n",
+            "Loss after epoch 37300 is 6.158289\n",
+            "Loss after epoch 37350 is 6.146099\n",
+            "Loss after epoch 37400 is 6.133947\n",
+            "Loss after epoch 37450 is 6.12185\n",
+            "Loss after epoch 37500 is 6.10978\n",
+            "Loss after epoch 37550 is 6.097728\n",
+            "Loss after epoch 37600 is 6.085694\n",
+            "Loss after epoch 37650 is 6.0736694\n",
+            "Loss after epoch 37700 is 6.0617213\n",
+            "Loss after epoch 37750 is 6.049802\n",
+            "Loss after epoch 37800 is 6.037884\n",
+            "Loss after epoch 37850 is 6.025973\n",
+            "Loss after epoch 37900 is 6.014111\n",
+            "Loss after epoch 37950 is 6.002307\n",
+            "Loss after epoch 38000 is 5.990502\n",
+            "Loss after epoch 38050 is 5.978728\n",
+            "Loss after epoch 38100 is 5.9669485\n",
+            "Loss after epoch 38150 is 5.9552464\n",
+            "Loss after epoch 38200 is 5.9435773\n",
+            "Loss after epoch 38250 is 5.931912\n",
+            "Loss after epoch 38300 is 5.920269\n",
+            "Loss after epoch 38350 is 5.908628\n",
+            "Loss after epoch 38400 is 5.897071\n",
+            "Loss after epoch 38450 is 5.8855247\n",
+            "Loss after epoch 38500 is 5.873994\n",
+            "Loss after epoch 38550 is 5.862472\n",
+            "Loss after epoch 38600 is 5.851006\n",
+            "Loss after epoch 38650 is 5.8395667\n",
+            "Loss after epoch 38700 is 5.828153\n",
+            "Loss after epoch 38750 is 5.8167434\n",
+            "Loss after epoch 38800 is 5.805351\n",
+            "Loss after epoch 38850 is 5.794033\n",
+            "Loss after epoch 38900 is 5.7827215\n",
+            "Loss after epoch 38950 is 5.7714443\n",
+            "Loss after epoch 39000 is 5.760165\n",
+            "Loss after epoch 39050 is 5.748919\n",
+            "Loss after epoch 39100 is 5.737723\n",
+            "Loss after epoch 39150 is 5.7265515\n",
+            "Loss after epoch 39200 is 5.7153926\n",
+            "Loss after epoch 39250 is 5.7042456\n",
+            "Loss after epoch 39300 is 5.6931334\n",
+            "Loss after epoch 39350 is 5.6820674\n",
+            "Loss after epoch 39400 is 5.6710277\n",
+            "Loss after epoch 39450 is 5.6599975\n",
+            "Loss after epoch 39500 is 5.6489773\n",
+            "Loss after epoch 39550 is 5.6379986\n",
+            "Loss after epoch 39600 is 5.6270638\n",
+            "Loss after epoch 39650 is 5.6161437\n",
+            "Loss after epoch 39700 is 5.605234\n",
+            "Loss after epoch 39750 is 5.594359\n",
+            "Loss after epoch 39800 is 5.583513\n",
+            "Loss after epoch 39850 is 5.5727015\n",
+            "Loss after epoch 39900 is 5.5619187\n",
+            "Loss after epoch 39950 is 5.5511293\n",
+            "Loss after epoch 40000 is 5.5403595\n",
+            "Loss after epoch 40050 is 5.5296636\n",
+            "Loss after epoch 40100 is 5.5189734\n",
+            "Loss after epoch 40150 is 5.50831\n",
+            "Loss after epoch 40200 is 5.4976435\n",
+            "Loss after epoch 40250 is 5.4870124\n",
+            "Loss after epoch 40300 is 5.4764233\n",
+            "Loss after epoch 40350 is 5.465869\n",
+            "Loss after epoch 40400 is 5.4553204\n",
+            "Loss after epoch 40450 is 5.4447737\n",
+            "Loss after epoch 40500 is 5.434271\n",
+            "Loss after epoch 40550 is 5.4238167\n",
+            "Loss after epoch 40600 is 5.413378\n",
+            "Loss after epoch 40650 is 5.4029517\n",
+            "Loss after epoch 40700 is 5.3925357\n",
+            "Loss after epoch 40750 is 5.3821487\n",
+            "Loss after epoch 40800 is 5.3718243\n",
+            "Loss after epoch 40850 is 5.3615\n",
+            "Loss after epoch 40900 is 5.351192\n",
+            "Loss after epoch 40950 is 5.3408957\n",
+            "Loss after epoch 41000 is 5.3306355\n",
+            "Loss after epoch 41050 is 5.320417\n",
+            "Loss after epoch 41100 is 5.3102283\n",
+            "Loss after epoch 41150 is 5.3000364\n",
+            "Loss after epoch 41200 is 5.2898607\n",
+            "Loss after epoch 41250 is 5.27973\n",
+            "Loss after epoch 41300 is 5.269627\n",
+            "Loss after epoch 41350 is 5.259549\n",
+            "Loss after epoch 41400 is 5.249473\n",
+            "Loss after epoch 41450 is 5.2394214\n",
+            "Loss after epoch 41500 is 5.229395\n",
+            "Loss after epoch 41550 is 5.219424\n",
+            "Loss after epoch 41600 is 5.2094607\n",
+            "Loss after epoch 41650 is 5.1995144\n",
+            "Loss after epoch 41700 is 5.189558\n",
+            "Loss after epoch 41750 is 5.1796594\n",
+            "Loss after epoch 41800 is 5.169802\n",
+            "Loss after epoch 41850 is 5.159956\n",
+            "Loss after epoch 41900 is 5.15012\n",
+            "Loss after epoch 41950 is 5.140296\n",
+            "Loss after epoch 42000 is 5.130499\n",
+            "Loss after epoch 42050 is 5.120755\n",
+            "Loss after epoch 42100 is 5.1110187\n",
+            "Loss after epoch 42150 is 5.1013103\n",
+            "Loss after epoch 42200 is 5.0915947\n",
+            "Loss after epoch 42250 is 5.0819106\n",
+            "Loss after epoch 42300 is 5.072277\n",
+            "Loss after epoch 42350 is 5.0626636\n",
+            "Loss after epoch 42400 is 5.053055\n",
+            "Loss after epoch 42450 is 5.0434656\n",
+            "Loss after epoch 42500 is 5.0338855\n",
+            "Loss after epoch 42550 is 5.0243716\n",
+            "Loss after epoch 42600 is 5.0148754\n",
+            "Loss after epoch 42650 is 5.0053706\n",
+            "Loss after epoch 42700 is 4.9958925\n",
+            "Loss after epoch 42750 is 4.9864287\n",
+            "Loss after epoch 42800 is 4.977026\n",
+            "Loss after epoch 42850 is 4.9676194\n",
+            "Loss after epoch 42900 is 4.958237\n",
+            "Loss after epoch 42950 is 4.94887\n",
+            "Loss after epoch 43000 is 4.9395165\n",
+            "Loss after epoch 43050 is 4.9302077\n",
+            "Loss after epoch 43100 is 4.920943\n",
+            "Loss after epoch 43150 is 4.9116707\n",
+            "Loss after epoch 43200 is 4.9024096\n",
+            "Loss after epoch 43250 is 4.8931603\n",
+            "Loss after epoch 43300 is 4.8839593\n",
+            "Loss after epoch 43350 is 4.874786\n",
+            "Loss after epoch 43400 is 4.8656197\n",
+            "Loss after epoch 43450 is 4.856484\n",
+            "Loss after epoch 43500 is 4.8473415\n",
+            "Loss after epoch 43550 is 4.8382344\n",
+            "Loss after epoch 43600 is 4.8291783\n",
+            "Loss after epoch 43650 is 4.8201203\n",
+            "Loss after epoch 43700 is 4.811085\n",
+            "Loss after epoch 43750 is 4.802051\n",
+            "Loss after epoch 43800 is 4.793043\n",
+            "Loss after epoch 43850 is 4.7840962\n",
+            "Loss after epoch 43900 is 4.7751417\n",
+            "Loss after epoch 43950 is 4.7662163\n",
+            "Loss after epoch 44000 is 4.757295\n",
+            "Loss after epoch 44050 is 4.74839\n",
+            "Loss after epoch 44100 is 4.739529\n",
+            "Loss after epoch 44150 is 4.730694\n",
+            "Loss after epoch 44200 is 4.7218733\n",
+            "Loss after epoch 44250 is 4.7130585\n",
+            "Loss after epoch 44300 is 4.7042527\n",
+            "Loss after epoch 44350 is 4.6954947\n",
+            "Loss after epoch 44400 is 4.686761\n",
+            "Loss after epoch 44450 is 4.6780453\n",
+            "Loss after epoch 44500 is 4.6693335\n",
+            "Loss after epoch 44550 is 4.660631\n",
+            "Loss after epoch 44600 is 4.6519604\n",
+            "Loss after epoch 44650 is 4.643334\n",
+            "Loss after epoch 44700 is 4.634729\n",
+            "Loss after epoch 44750 is 4.626118\n",
+            "Loss after epoch 44800 is 4.6175213\n",
+            "Loss after epoch 44850 is 4.608947\n",
+            "Loss after epoch 44900 is 4.600414\n",
+            "Loss after epoch 44950 is 4.591895\n",
+            "Loss after epoch 45000 is 4.583406\n",
+            "Loss after epoch 45050 is 4.5749216\n",
+            "Loss after epoch 45100 is 4.566434\n",
+            "Loss after epoch 45150 is 4.557984\n",
+            "Loss after epoch 45200 is 4.5495834\n",
+            "Loss after epoch 45250 is 4.5411925\n",
+            "Loss after epoch 45300 is 4.5327992\n",
+            "Loss after epoch 45350 is 4.5244207\n",
+            "Loss after epoch 45400 is 4.5160594\n",
+            "Loss after epoch 45450 is 4.507754\n",
+            "Loss after epoch 45500 is 4.4994583\n",
+            "Loss after epoch 45550 is 4.491178\n",
+            "Loss after epoch 45600 is 4.4829006\n",
+            "Loss after epoch 45650 is 4.4746375\n",
+            "Loss after epoch 45700 is 4.4663954\n",
+            "Loss after epoch 45750 is 4.4582067\n",
+            "Loss after epoch 45800 is 4.450019\n",
+            "Loss after epoch 45850 is 4.4418554\n",
+            "Loss after epoch 45900 is 4.4336944\n",
+            "Loss after epoch 45950 is 4.425536\n",
+            "Loss after epoch 46000 is 4.4174347\n",
+            "Loss after epoch 46050 is 4.409361\n",
+            "Loss after epoch 46100 is 4.401283\n",
+            "Loss after epoch 46150 is 4.393225\n",
+            "Loss after epoch 46200 is 4.3851695\n",
+            "Loss after epoch 46250 is 4.3771367\n",
+            "Loss after epoch 46300 is 4.369162\n",
+            "Loss after epoch 46350 is 4.3611794\n",
+            "Loss after epoch 46400 is 4.3532248\n",
+            "Loss after epoch 46450 is 4.34527\n",
+            "Loss after epoch 46500 is 4.3373346\n",
+            "Loss after epoch 46550 is 4.329418\n",
+            "Loss after epoch 46600 is 4.321548\n",
+            "Loss after epoch 46650 is 4.3136845\n",
+            "Loss after epoch 46700 is 4.305833\n",
+            "Loss after epoch 46750 is 4.2979856\n",
+            "Loss after epoch 46800 is 4.290157\n",
+            "Loss after epoch 46850 is 4.282368\n",
+            "Loss after epoch 46900 is 4.2746058\n",
+            "Loss after epoch 46950 is 4.2668395\n",
+            "Loss after epoch 47000 is 4.2591057\n",
+            "Loss after epoch 47050 is 4.2513623\n",
+            "Loss after epoch 47100 is 4.243639\n",
+            "Loss after epoch 47150 is 4.2359667\n",
+            "Loss after epoch 47200 is 4.2283144\n",
+            "Loss after epoch 47250 is 4.2206597\n",
+            "Loss after epoch 47300 is 4.213019\n",
+            "Loss after epoch 47350 is 4.2053847\n",
+            "Loss after epoch 47400 is 4.197782\n",
+            "Loss after epoch 47450 is 4.190225\n",
+            "Loss after epoch 47500 is 4.1826615\n",
+            "Loss after epoch 47550 is 4.175118\n",
+            "Loss after epoch 47600 is 4.167579\n",
+            "Loss after epoch 47650 is 4.160053\n",
+            "Loss after epoch 47700 is 4.1525626\n",
+            "Loss after epoch 47750 is 4.1451054\n",
+            "Loss after epoch 47800 is 4.137654\n",
+            "Loss after epoch 47850 is 4.130212\n",
+            "Loss after epoch 47900 is 4.122782\n",
+            "Loss after epoch 47950 is 4.1153445\n",
+            "Loss after epoch 48000 is 4.107983\n",
+            "Loss after epoch 48050 is 4.100624\n",
+            "Loss after epoch 48100 is 4.093271\n",
+            "Loss after epoch 48150 is 4.0859313\n",
+            "Loss after epoch 48200 is 4.078599\n",
+            "Loss after epoch 48250 is 4.0712757\n",
+            "Loss after epoch 48300 is 4.0640044\n",
+            "Loss after epoch 48350 is 4.056761\n",
+            "Loss after epoch 48400 is 4.0495076\n",
+            "Loss after epoch 48450 is 4.042268\n",
+            "Loss after epoch 48500 is 4.0350304\n",
+            "Loss after epoch 48550 is 4.0278254\n",
+            "Loss after epoch 48600 is 4.020656\n",
+            "Loss after epoch 48650 is 4.0135055\n",
+            "Loss after epoch 48700 is 4.006352\n",
+            "Loss after epoch 48750 is 3.999221\n",
+            "Loss after epoch 48800 is 3.992085\n",
+            "Loss after epoch 48850 is 3.9849706\n",
+            "Loss after epoch 48900 is 3.9779043\n",
+            "Loss after epoch 48950 is 3.9708493\n",
+            "Loss after epoch 49000 is 3.9638073\n",
+            "Loss after epoch 49050 is 3.956756\n",
+            "Loss after epoch 49100 is 3.9497316\n",
+            "Loss after epoch 49150 is 3.9427223\n",
+            "Loss after epoch 49200 is 3.9357584\n",
+            "Loss after epoch 49250 is 3.9288023\n",
+            "Loss after epoch 49300 is 3.9218378\n",
+            "Loss after epoch 49350 is 3.914897\n",
+            "Loss after epoch 49400 is 3.9079638\n",
+            "Loss after epoch 49450 is 3.9010508\n",
+            "Loss after epoch 49500 is 3.8941777\n",
+            "Loss after epoch 49550 is 3.887318\n",
+            "Loss after epoch 49600 is 3.8804762\n",
+            "Loss after epoch 49650 is 3.8736296\n",
+            "Loss after epoch 49700 is 3.86679\n",
+            "Loss after epoch 49750 is 3.859968\n",
+            "Loss after epoch 49800 is 3.8531907\n",
+            "Loss after epoch 49850 is 3.8464336\n",
+            "Loss after epoch 49900 is 3.8396757\n",
+            "Loss after epoch 49950 is 3.8329346\n",
+            "Loss after epoch 50000 is 3.826188\n",
+            "Loss after epoch 50050 is 3.819452\n",
+            "Loss after epoch 50100 is 3.8127787\n",
+            "Loss after epoch 50150 is 3.8061047\n",
+            "Loss after epoch 50200 is 3.7994502\n",
+            "Loss after epoch 50250 is 3.7928014\n",
+            "Loss after epoch 50300 is 3.786149\n",
+            "Loss after epoch 50350 is 3.7795148\n",
+            "Loss after epoch 50400 is 3.772928\n",
+            "Loss after epoch 50450 is 3.7663581\n",
+            "Loss after epoch 50500 is 3.7597787\n",
+            "Loss after epoch 50550 is 3.7532248\n",
+            "Loss after epoch 50600 is 3.7466762\n",
+            "Loss after epoch 50650 is 3.7401314\n",
+            "Loss after epoch 50700 is 3.7336287\n",
+            "Loss after epoch 50750 is 3.7271445\n",
+            "Loss after epoch 50800 is 3.720672\n",
+            "Loss after epoch 50850 is 3.7142055\n",
+            "Loss after epoch 50900 is 3.7077487\n",
+            "Loss after epoch 50950 is 3.7012937\n",
+            "Loss after epoch 51000 is 3.6948748\n",
+            "Loss after epoch 51050 is 3.6884868\n",
+            "Loss after epoch 51100 is 3.6821003\n",
+            "Loss after epoch 51150 is 3.6757364\n",
+            "Loss after epoch 51200 is 3.669365\n",
+            "Loss after epoch 51250 is 3.6630075\n",
+            "Loss after epoch 51300 is 3.6566591\n",
+            "Loss after epoch 51350 is 3.6503675\n",
+            "Loss after epoch 51400 is 3.6440728\n",
+            "Loss after epoch 51450 is 3.6377995\n",
+            "Loss after epoch 51500 is 3.631519\n",
+            "Loss after epoch 51550 is 3.6252565\n",
+            "Loss after epoch 51600 is 3.61899\n",
+            "Loss after epoch 51650 is 3.612775\n",
+            "Loss after epoch 51700 is 3.6065822\n",
+            "Loss after epoch 51750 is 3.60038\n",
+            "Loss after epoch 51800 is 3.5942025\n",
+            "Loss after epoch 51850 is 3.5880246\n",
+            "Loss after epoch 51900 is 3.5818448\n",
+            "Loss after epoch 51950 is 3.5757139\n",
+            "Loss after epoch 52000 is 3.5696058\n",
+            "Loss after epoch 52050 is 3.5635028\n",
+            "Loss after epoch 52100 is 3.5573943\n",
+            "Loss after epoch 52150 is 3.5513074\n",
+            "Loss after epoch 52200 is 3.545228\n",
+            "Loss after epoch 52250 is 3.5391545\n",
+            "Loss after epoch 52300 is 3.53313\n",
+            "Loss after epoch 52350 is 3.527113\n",
+            "Loss after epoch 52400 is 3.5211177\n",
+            "Loss after epoch 52450 is 3.5151153\n",
+            "Loss after epoch 52500 is 3.509117\n",
+            "Loss after epoch 52550 is 3.50313\n",
+            "Loss after epoch 52600 is 3.4971805\n",
+            "Loss after epoch 52650 is 3.4912496\n",
+            "Loss after epoch 52700 is 3.4853241\n",
+            "Loss after epoch 52750 is 3.4794202\n",
+            "Loss after epoch 52800 is 3.473507\n",
+            "Loss after epoch 52850 is 3.467606\n",
+            "Loss after epoch 52900 is 3.4617238\n",
+            "Loss after epoch 52950 is 3.4558768\n",
+            "Loss after epoch 53000 is 3.4500463\n",
+            "Loss after epoch 53050 is 3.4442122\n",
+            "Loss after epoch 53100 is 3.4383948\n",
+            "Loss after epoch 53150 is 3.4325755\n",
+            "Loss after epoch 53200 is 3.4267745\n",
+            "Loss after epoch 53250 is 3.4209945\n",
+            "Loss after epoch 53300 is 3.4152458\n",
+            "Loss after epoch 53350 is 3.4095082\n",
+            "Loss after epoch 53400 is 3.4037755\n",
+            "Loss after epoch 53450 is 3.398037\n",
+            "Loss after epoch 53500 is 3.392319\n",
+            "Loss after epoch 53550 is 3.386605\n",
+            "Loss after epoch 53600 is 3.3809319\n",
+            "Loss after epoch 53650 is 3.3752744\n",
+            "Loss after epoch 53700 is 3.3696232\n",
+            "Loss after epoch 53750 is 3.3639796\n",
+            "Loss after epoch 53800 is 3.358343\n",
+            "Loss after epoch 53850 is 3.3527122\n",
+            "Loss after epoch 53900 is 3.3470953\n",
+            "Loss after epoch 53950 is 3.3415217\n",
+            "Loss after epoch 54000 is 3.335949\n",
+            "Loss after epoch 54050 is 3.3303862\n",
+            "Loss after epoch 54100 is 3.3248417\n",
+            "Loss after epoch 54150 is 3.3192885\n",
+            "Loss after epoch 54200 is 3.3137465\n",
+            "Loss after epoch 54250 is 3.308233\n",
+            "Loss after epoch 54300 is 3.3027437\n",
+            "Loss after epoch 54350 is 3.2972693\n",
+            "Loss after epoch 54400 is 3.291793\n",
+            "Loss after epoch 54450 is 3.2863352\n",
+            "Loss after epoch 54500 is 3.280871\n",
+            "Loss after epoch 54550 is 3.2754228\n",
+            "Loss after epoch 54600 is 3.2700067\n",
+            "Loss after epoch 54650 is 3.2646015\n",
+            "Loss after epoch 54700 is 3.2592132\n",
+            "Loss after epoch 54750 is 3.2538278\n",
+            "Loss after epoch 54800 is 3.24845\n",
+            "Loss after epoch 54850 is 3.243079\n",
+            "Loss after epoch 54900 is 3.2377062\n",
+            "Loss after epoch 54950 is 3.2323837\n",
+            "Loss after epoch 55000 is 3.227075\n",
+            "Loss after epoch 55050 is 3.2217736\n",
+            "Loss after epoch 55100 is 3.2164776\n",
+            "Loss after epoch 55150 is 3.2111833\n",
+            "Loss after epoch 55200 is 3.2059\n",
+            "Loss after epoch 55250 is 3.200622\n",
+            "Loss after epoch 55300 is 3.1953893\n",
+            "Loss after epoch 55350 is 3.190163\n",
+            "Loss after epoch 55400 is 3.1849477\n",
+            "Loss after epoch 55450 is 3.1797345\n",
+            "Loss after epoch 55500 is 3.1745265\n",
+            "Loss after epoch 55550 is 3.169324\n",
+            "Loss after epoch 55600 is 3.1641288\n",
+            "Loss after epoch 55650 is 3.1589909\n",
+            "Loss after epoch 55700 is 3.153848\n",
+            "Loss after epoch 55750 is 3.148711\n",
+            "Loss after epoch 55800 is 3.1435897\n",
+            "Loss after epoch 55850 is 3.1384628\n",
+            "Loss after epoch 55900 is 3.1333463\n",
+            "Loss after epoch 55950 is 3.1282442\n",
+            "Loss after epoch 56000 is 3.1231787\n",
+            "Loss after epoch 56050 is 3.1181252\n",
+            "Loss after epoch 56100 is 3.113071\n",
+            "Loss after epoch 56150 is 3.1080308\n",
+            "Loss after epoch 56200 is 3.1029835\n",
+            "Loss after epoch 56250 is 3.0979574\n",
+            "Loss after epoch 56300 is 3.0929272\n",
+            "Loss after epoch 56350 is 3.0879514\n",
+            "Loss after epoch 56400 is 3.082979\n",
+            "Loss after epoch 56450 is 3.078014\n",
+            "Loss after epoch 56500 is 3.0730433\n",
+            "Loss after epoch 56550 is 3.0680923\n",
+            "Loss after epoch 56600 is 3.0631435\n",
+            "Loss after epoch 56650 is 3.058203\n",
+            "Loss after epoch 56700 is 3.0532978\n",
+            "Loss after epoch 56750 is 3.0484061\n",
+            "Loss after epoch 56800 is 3.0435207\n",
+            "Loss after epoch 56850 is 3.0386405\n",
+            "Loss after epoch 56900 is 3.0337672\n",
+            "Loss after epoch 56950 is 3.0288994\n",
+            "Loss after epoch 57000 is 3.0240276\n",
+            "Loss after epoch 57050 is 3.019199\n",
+            "Loss after epoch 57100 is 3.0143878\n",
+            "Loss after epoch 57150 is 3.0095806\n",
+            "Loss after epoch 57200 is 3.0047886\n",
+            "Loss after epoch 57250 is 2.9999945\n",
+            "Loss after epoch 57300 is 2.9952013\n",
+            "Loss after epoch 57350 is 2.9904191\n",
+            "Loss after epoch 57400 is 2.9856572\n",
+            "Loss after epoch 57450 is 2.980924\n",
+            "Loss after epoch 57500 is 2.9762027\n",
+            "Loss after epoch 57550 is 2.9714816\n",
+            "Loss after epoch 57600 is 2.9667728\n",
+            "Loss after epoch 57650 is 2.9620569\n",
+            "Loss after epoch 57700 is 2.9573514\n",
+            "Loss after epoch 57750 is 2.9526656\n",
+            "Loss after epoch 57800 is 2.9480064\n",
+            "Loss after epoch 57850 is 2.9433608\n",
+            "Loss after epoch 57900 is 2.9387262\n",
+            "Loss after epoch 57950 is 2.9340847\n",
+            "Loss after epoch 58000 is 2.929455\n",
+            "Loss after epoch 58050 is 2.924824\n",
+            "Loss after epoch 58100 is 2.9202101\n",
+            "Loss after epoch 58150 is 2.915625\n",
+            "Loss after epoch 58200 is 2.9110556\n",
+            "Loss after epoch 58250 is 2.906492\n",
+            "Loss after epoch 58300 is 2.9019368\n",
+            "Loss after epoch 58350 is 2.8973753\n",
+            "Loss after epoch 58400 is 2.8928275\n",
+            "Loss after epoch 58450 is 2.8882895\n",
+            "Loss after epoch 58500 is 2.8837662\n",
+            "Loss after epoch 58550 is 2.879273\n",
+            "Loss after epoch 58600 is 2.8747847\n",
+            "Loss after epoch 58650 is 2.8703005\n",
+            "Loss after epoch 58700 is 2.8658257\n",
+            "Loss after epoch 58750 is 2.861356\n",
+            "Loss after epoch 58800 is 2.856888\n",
+            "Loss after epoch 58850 is 2.8524256\n",
+            "Loss after epoch 58900 is 2.848007\n",
+            "Loss after epoch 58950 is 2.8435898\n",
+            "Loss after epoch 59000 is 2.839185\n",
+            "Loss after epoch 59050 is 2.8347774\n",
+            "Loss after epoch 59100 is 2.8303902\n",
+            "Loss after epoch 59150 is 2.8259966\n",
+            "Loss after epoch 59200 is 2.8216062\n",
+            "Loss after epoch 59250 is 2.817236\n",
+            "Loss after epoch 59300 is 2.8129041\n",
+            "Loss after epoch 59350 is 2.8085654\n",
+            "Loss after epoch 59400 is 2.8042452\n",
+            "Loss after epoch 59450 is 2.799919\n",
+            "Loss after epoch 59500 is 2.7956061\n",
+            "Loss after epoch 59550 is 2.791291\n",
+            "Loss after epoch 59600 is 2.78699\n",
+            "Loss after epoch 59650 is 2.7827125\n",
+            "Loss after epoch 59700 is 2.7784588\n",
+            "Loss after epoch 59750 is 2.7741969\n",
+            "Loss after epoch 59800 is 2.7699523\n",
+            "Loss after epoch 59850 is 2.7657125\n",
+            "Loss after epoch 59900 is 2.7614665\n",
+            "Loss after epoch 59950 is 2.7572348\n",
+            "Loss after epoch 60000 is 2.753004\n",
+            "Loss after epoch 60050 is 2.748823\n",
+            "Loss after epoch 60100 is 2.7446434\n",
+            "Loss after epoch 60150 is 2.7404687\n",
+            "Loss after epoch 60200 is 2.736298\n",
+            "Loss after epoch 60250 is 2.7321343\n",
+            "Loss after epoch 60300 is 2.7279742\n",
+            "Loss after epoch 60350 is 2.723809\n",
+            "Loss after epoch 60400 is 2.7196672\n",
+            "Loss after epoch 60450 is 2.7155552\n",
+            "Loss after epoch 60500 is 2.7114618\n",
+            "Loss after epoch 60550 is 2.7073615\n",
+            "Loss after epoch 60600 is 2.7032633\n",
+            "Loss after epoch 60650 is 2.699176\n",
+            "Loss after epoch 60700 is 2.6950877\n",
+            "Loss after epoch 60750 is 2.6910062\n",
+            "Loss after epoch 60800 is 2.6869464\n",
+            "Loss after epoch 60850 is 2.6829195\n",
+            "Loss after epoch 60900 is 2.6788838\n",
+            "Loss after epoch 60950 is 2.6748593\n",
+            "Loss after epoch 61000 is 2.6708474\n",
+            "Loss after epoch 61050 is 2.6668298\n",
+            "Loss after epoch 61100 is 2.6628149\n",
+            "Loss after epoch 61150 is 2.658816\n",
+            "Loss after epoch 61200 is 2.654834\n",
+            "Loss after epoch 61250 is 2.650869\n",
+            "Loss after epoch 61300 is 2.6469235\n",
+            "Loss after epoch 61350 is 2.6429727\n",
+            "Loss after epoch 61400 is 2.6390254\n",
+            "Loss after epoch 61450 is 2.6350882\n",
+            "Loss after epoch 61500 is 2.6311476\n",
+            "Loss after epoch 61550 is 2.6272223\n",
+            "Loss after epoch 61600 is 2.6233108\n",
+            "Loss after epoch 61650 is 2.6194272\n",
+            "Loss after epoch 61700 is 2.6155457\n",
+            "Loss after epoch 61750 is 2.6116745\n",
+            "Loss after epoch 61800 is 2.6077986\n",
+            "Loss after epoch 61850 is 2.6039314\n",
+            "Loss after epoch 61900 is 2.6000707\n",
+            "Loss after epoch 61950 is 2.5962105\n",
+            "Loss after epoch 62000 is 2.5923722\n",
+            "Loss after epoch 62050 is 2.5885592\n",
+            "Loss after epoch 62100 is 2.5847507\n",
+            "Loss after epoch 62150 is 2.580959\n",
+            "Loss after epoch 62200 is 2.577157\n",
+            "Loss after epoch 62250 is 2.5733619\n",
+            "Loss after epoch 62300 is 2.5695736\n",
+            "Loss after epoch 62350 is 2.5657856\n",
+            "Loss after epoch 62400 is 2.562007\n",
+            "Loss after epoch 62450 is 2.5582752\n",
+            "Loss after epoch 62500 is 2.5545325\n",
+            "Loss after epoch 62550 is 2.5508018\n",
+            "Loss after epoch 62600 is 2.5470705\n",
+            "Loss after epoch 62650 is 2.543354\n",
+            "Loss after epoch 62700 is 2.5396304\n",
+            "Loss after epoch 62750 is 2.5359159\n",
+            "Loss after epoch 62800 is 2.532205\n",
+            "Loss after epoch 62850 is 2.5285401\n",
+            "Loss after epoch 62900 is 2.52487\n",
+            "Loss after epoch 62950 is 2.5212119\n",
+            "Loss after epoch 63000 is 2.5175505\n",
+            "Loss after epoch 63050 is 2.5139031\n",
+            "Loss after epoch 63100 is 2.5102518\n",
+            "Loss after epoch 63150 is 2.5066123\n",
+            "Loss after epoch 63200 is 2.502967\n",
+            "Loss after epoch 63250 is 2.4993594\n",
+            "Loss after epoch 63300 is 2.495765\n",
+            "Loss after epoch 63350 is 2.4921644\n",
+            "Loss after epoch 63400 is 2.488581\n",
+            "Loss after epoch 63450 is 2.4849992\n",
+            "Loss after epoch 63500 is 2.481414\n",
+            "Loss after epoch 63550 is 2.4778402\n",
+            "Loss after epoch 63600 is 2.474271\n",
+            "Loss after epoch 63650 is 2.4707162\n",
+            "Loss after epoch 63700 is 2.4671907\n",
+            "Loss after epoch 63750 is 2.4636664\n",
+            "Loss after epoch 63800 is 2.4601455\n",
+            "Loss after epoch 63850 is 2.45663\n",
+            "Loss after epoch 63900 is 2.4531214\n",
+            "Loss after epoch 63950 is 2.449615\n",
+            "Loss after epoch 64000 is 2.4461129\n",
+            "Loss after epoch 64050 is 2.4426036\n",
+            "Loss after epoch 64100 is 2.4391499\n",
+            "Loss after epoch 64150 is 2.4356916\n",
+            "Loss after epoch 64200 is 2.432236\n",
+            "Loss after epoch 64250 is 2.4287884\n",
+            "Loss after epoch 64300 is 2.4253445\n",
+            "Loss after epoch 64350 is 2.4219024\n",
+            "Loss after epoch 64400 is 2.418464\n",
+            "Loss after epoch 64450 is 2.4150338\n",
+            "Loss after epoch 64500 is 2.4116173\n",
+            "Loss after epoch 64550 is 2.408234\n",
+            "Loss after epoch 64600 is 2.404843\n",
+            "Loss after epoch 64650 is 2.4014578\n",
+            "Loss after epoch 64700 is 2.398086\n",
+            "Loss after epoch 64750 is 2.3947108\n",
+            "Loss after epoch 64800 is 2.391336\n",
+            "Loss after epoch 64850 is 2.3879757\n",
+            "Loss after epoch 64900 is 2.384609\n",
+            "Loss after epoch 64950 is 2.3812804\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 2.087589\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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VyYSx91skz56P4i4NPoorCW0hhCggiqKw+o+PmHl4GoqiMPeFIN5p/J5N2mlq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\nkYNgaBMRETmI/wP1SKGtGk4/SgAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57def6a90>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "8PHvAxPMvahu",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 32301
+        },
+        "outputId": "febf1283-6bbe-404e-d99d-5be28117bd33"
+      },
+      "cell_type": "code",
+      "source": [
+        "linear_regression(learning_rate=0.000033,n_epochs=95000,interval=50)"
+      ],
+      "execution_count": 34,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Loss after epoch 0 is 48307.223\n",
+            "Loss after epoch 50 is 30.72802\n",
+            "Loss after epoch 100 is 30.658358\n",
+            "Loss after epoch 150 is 30.5889\n",
+            "Loss after epoch 200 is 30.519617\n",
+            "Loss after epoch 250 is 30.450468\n",
+            "Loss after epoch 300 is 30.381456\n",
+            "Loss after epoch 350 is 30.312628\n",
+            "Loss after epoch 400 is 30.24399\n",
+            "Loss after epoch 450 is 30.17551\n",
+            "Loss after epoch 500 is 30.107164\n",
+            "Loss after epoch 550 is 30.038965\n",
+            "Loss after epoch 600 is 29.970926\n",
+            "Loss after epoch 650 is 29.903082\n",
+            "Loss after epoch 700 is 29.835356\n",
+            "Loss after epoch 750 is 29.767813\n",
+            "Loss after epoch 800 is 29.70044\n",
+            "Loss after epoch 850 is 29.63321\n",
+            "Loss after epoch 900 is 29.56615\n",
+            "Loss after epoch 950 is 29.499212\n",
+            "Loss after epoch 1000 is 29.432459\n",
+            "Loss after epoch 1050 is 29.36584\n",
+            "Loss after epoch 1100 is 29.299385\n",
+            "Loss after epoch 1150 is 29.233116\n",
+            "Loss after epoch 1200 is 29.16696\n",
+            "Loss after epoch 1250 is 29.100985\n",
+            "Loss after epoch 1300 is 29.035173\n",
+            "Loss after epoch 1350 is 28.969479\n",
+            "Loss after epoch 1400 is 28.903992\n",
+            "Loss after epoch 1450 is 28.838606\n",
+            "Loss after epoch 1500 is 28.773384\n",
+            "Loss after epoch 1550 is 28.708313\n",
+            "Loss after epoch 1600 is 28.643438\n",
+            "Loss after epoch 1650 is 28.57866\n",
+            "Loss after epoch 1700 is 28.514074\n",
+            "Loss after epoch 1750 is 28.449596\n",
+            "Loss after epoch 1800 is 28.38529\n",
+            "Loss after epoch 1850 is 28.321146\n",
+            "Loss after epoch 1900 is 28.25714\n",
+            "Loss after epoch 1950 is 28.193277\n",
+            "Loss after epoch 2000 is 28.129574\n",
+            "Loss after epoch 2050 is 28.066036\n",
+            "Loss after epoch 2100 is 28.002615\n",
+            "Loss after epoch 2150 is 27.939367\n",
+            "Loss after epoch 2200 is 27.876244\n",
+            "Loss after epoch 2250 is 27.813282\n",
+            "Loss after epoch 2300 is 27.75048\n",
+            "Loss after epoch 2350 is 27.687794\n",
+            "Loss after epoch 2400 is 27.625282\n",
+            "Loss after epoch 2450 is 27.5629\n",
+            "Loss after epoch 2500 is 27.500666\n",
+            "Loss after epoch 2550 is 27.438585\n",
+            "Loss after epoch 2600 is 27.37664\n",
+            "Loss after epoch 2650 is 27.314837\n",
+            "Loss after epoch 2700 is 27.253174\n",
+            "Loss after epoch 2750 is 27.191666\n",
+            "Loss after epoch 2800 is 27.130318\n",
+            "Loss after epoch 2850 is 27.069122\n",
+            "Loss after epoch 2900 is 27.008007\n",
+            "Loss after epoch 2950 is 26.947092\n",
+            "Loss after epoch 3000 is 26.8863\n",
+            "Loss after epoch 3050 is 26.825657\n",
+            "Loss after epoch 3100 is 26.765131\n",
+            "Loss after epoch 3150 is 26.704763\n",
+            "Loss after epoch 3200 is 26.64457\n",
+            "Loss after epoch 3250 is 26.584473\n",
+            "Loss after epoch 3300 is 26.524542\n",
+            "Loss after epoch 3350 is 26.464752\n",
+            "Loss after epoch 3400 is 26.405075\n",
+            "Loss after epoch 3450 is 26.345572\n",
+            "Loss after epoch 3500 is 26.28616\n",
+            "Loss after epoch 3550 is 26.226923\n",
+            "Loss after epoch 3600 is 26.167795\n",
+            "Loss after epoch 3650 is 26.108868\n",
+            "Loss after epoch 3700 is 26.050035\n",
+            "Loss after epoch 3750 is 25.99132\n",
+            "Loss after epoch 3800 is 25.932777\n",
+            "Loss after epoch 3850 is 25.874353\n",
+            "Loss after epoch 3900 is 25.816076\n",
+            "Loss after epoch 3950 is 25.75793\n",
+            "Loss after epoch 4000 is 25.699942\n",
+            "Loss after epoch 4050 is 25.642044\n",
+            "Loss after epoch 4100 is 25.58432\n",
+            "Loss after epoch 4150 is 25.526709\n",
+            "Loss after epoch 4200 is 25.469238\n",
+            "Loss after epoch 4250 is 25.411898\n",
+            "Loss after epoch 4300 is 25.3547\n",
+            "Loss after epoch 4350 is 25.297636\n",
+            "Loss after epoch 4400 is 25.240711\n",
+            "Loss after epoch 4450 is 25.183905\n",
+            "Loss after epoch 4500 is 25.127241\n",
+            "Loss after epoch 4550 is 25.07069\n",
+            "Loss after epoch 4600 is 25.014284\n",
+            "Loss after epoch 4650 is 24.95803\n",
+            "Loss after epoch 4700 is 24.901913\n",
+            "Loss after epoch 4750 is 24.845905\n",
+            "Loss after epoch 4800 is 24.790009\n",
+            "Loss after epoch 4850 is 24.734247\n",
+            "Loss after epoch 4900 is 24.678637\n",
+            "Loss after epoch 4950 is 24.62317\n",
+            "Loss after epoch 5000 is 24.567812\n",
+            "Loss after epoch 5050 is 24.51259\n",
+            "Loss after epoch 5100 is 24.45749\n",
+            "Loss after epoch 5150 is 24.402506\n",
+            "Loss after epoch 5200 is 24.347683\n",
+            "Loss after epoch 5250 is 24.292961\n",
+            "Loss after epoch 5300 is 24.238375\n",
+            "Loss after epoch 5350 is 24.183939\n",
+            "Loss after epoch 5400 is 24.129608\n",
+            "Loss after epoch 5450 is 24.075405\n",
+            "Loss after epoch 5500 is 24.02132\n",
+            "Loss after epoch 5550 is 23.9674\n",
+            "Loss after epoch 5600 is 23.913546\n",
+            "Loss after epoch 5650 is 23.859875\n",
+            "Loss after epoch 5700 is 23.806295\n",
+            "Loss after epoch 5750 is 23.75286\n",
+            "Loss after epoch 5800 is 23.699535\n",
+            "Loss after epoch 5850 is 23.646338\n",
+            "Loss after epoch 5900 is 23.593292\n",
+            "Loss after epoch 5950 is 23.540327\n",
+            "Loss after epoch 6000 is 23.487501\n",
+            "Loss after epoch 6050 is 23.434792\n",
+            "Loss after epoch 6100 is 23.382248\n",
+            "Loss after epoch 6150 is 23.329763\n",
+            "Loss after epoch 6200 is 23.27745\n",
+            "Loss after epoch 6250 is 23.225239\n",
+            "Loss after epoch 6300 is 23.173151\n",
+            "Loss after epoch 6350 is 23.121187\n",
+            "Loss after epoch 6400 is 23.069351\n",
+            "Loss after epoch 6450 is 23.017628\n",
+            "Loss after epoch 6500 is 22.966019\n",
+            "Loss after epoch 6550 is 22.914534\n",
+            "Loss after epoch 6600 is 22.863192\n",
+            "Loss after epoch 6650 is 22.811949\n",
+            "Loss after epoch 6700 is 22.760834\n",
+            "Loss after epoch 6750 is 22.709848\n",
+            "Loss after epoch 6800 is 22.658949\n",
+            "Loss after epoch 6850 is 22.608192\n",
+            "Loss after epoch 6900 is 22.557531\n",
+            "Loss after epoch 6950 is 22.507046\n",
+            "Loss after epoch 7000 is 22.456604\n",
+            "Loss after epoch 7050 is 22.406336\n",
+            "Loss after epoch 7100 is 22.356167\n",
+            "Loss after epoch 7150 is 22.30612\n",
+            "Loss after epoch 7200 is 22.256178\n",
+            "Loss after epoch 7250 is 22.20635\n",
+            "Loss after epoch 7300 is 22.156662\n",
+            "Loss after epoch 7350 is 22.10705\n",
+            "Loss after epoch 7400 is 22.057589\n",
+            "Loss after epoch 7450 is 22.00825\n",
+            "Loss after epoch 7500 is 21.959028\n",
+            "Loss after epoch 7550 is 21.909904\n",
+            "Loss after epoch 7600 is 21.86087\n",
+            "Loss after epoch 7650 is 21.812002\n",
+            "Loss after epoch 7700 is 21.763186\n",
+            "Loss after epoch 7750 is 21.714537\n",
+            "Loss after epoch 7800 is 21.665966\n",
+            "Loss after epoch 7850 is 21.617533\n",
+            "Loss after epoch 7900 is 21.569216\n",
+            "Loss after epoch 7950 is 21.521006\n",
+            "Loss after epoch 8000 is 21.472914\n",
+            "Loss after epoch 8050 is 21.424938\n",
+            "Loss after epoch 8100 is 21.377043\n",
+            "Loss after epoch 8150 is 21.329279\n",
+            "Loss after epoch 8200 is 21.281624\n",
+            "Loss after epoch 8250 is 21.234116\n",
+            "Loss after epoch 8300 is 21.18665\n",
+            "Loss after epoch 8350 is 21.139345\n",
+            "Loss after epoch 8400 is 21.092142\n",
+            "Loss after epoch 8450 is 21.045048\n",
+            "Loss after epoch 8500 is 20.99808\n",
+            "Loss after epoch 8550 is 20.951195\n",
+            "Loss after epoch 8600 is 20.904444\n",
+            "Loss after epoch 8650 is 20.857767\n",
+            "Loss after epoch 8700 is 20.81121\n",
+            "Loss after epoch 8750 is 20.764786\n",
+            "Loss after epoch 8800 is 20.718464\n",
+            "Loss after epoch 8850 is 20.672235\n",
+            "Loss after epoch 8900 is 20.626131\n",
+            "Loss after epoch 8950 is 20.58011\n",
+            "Loss after epoch 9000 is 20.534199\n",
+            "Loss after epoch 9050 is 20.488415\n",
+            "Loss after epoch 9100 is 20.442745\n",
+            "Loss after epoch 9150 is 20.397165\n",
+            "Loss after epoch 9200 is 20.351665\n",
+            "Loss after epoch 9250 is 20.306316\n",
+            "Loss after epoch 9300 is 20.261059\n",
+            "Loss after epoch 9350 is 20.215906\n",
+            "Loss after epoch 9400 is 20.170843\n",
+            "Loss after epoch 9450 is 20.12593\n",
+            "Loss after epoch 9500 is 20.08107\n",
+            "Loss after epoch 9550 is 20.036354\n",
+            "Loss after epoch 9600 is 19.991726\n",
+            "Loss after epoch 9650 is 19.947205\n",
+            "Loss after epoch 9700 is 19.902807\n",
+            "Loss after epoch 9750 is 19.858482\n",
+            "Loss after epoch 9800 is 19.81428\n",
+            "Loss after epoch 9850 is 19.770151\n",
+            "Loss after epoch 9900 is 19.72614\n",
+            "Loss after epoch 9950 is 19.682247\n",
+            "Loss after epoch 10000 is 19.638454\n",
+            "Loss after epoch 10050 is 19.594753\n",
+            "Loss after epoch 10100 is 19.551157\n",
+            "Loss after epoch 10150 is 19.507685\n",
+            "Loss after epoch 10200 is 19.464277\n",
+            "Loss after epoch 10250 is 19.421001\n",
+            "Loss after epoch 10300 is 19.377787\n",
+            "Loss after epoch 10350 is 19.33473\n",
+            "Loss after epoch 10400 is 19.291748\n",
+            "Loss after epoch 10450 is 19.248842\n",
+            "Loss after epoch 10500 is 19.206076\n",
+            "Loss after epoch 10550 is 19.16339\n",
+            "Loss after epoch 10600 is 19.120792\n",
+            "Loss after epoch 10650 is 19.078325\n",
+            "Loss after epoch 10700 is 19.035938\n",
+            "Loss after epoch 10750 is 18.993618\n",
+            "Loss after epoch 10800 is 18.95145\n",
+            "Loss after epoch 10850 is 18.909369\n",
+            "Loss after epoch 10900 is 18.86735\n",
+            "Loss after epoch 10950 is 18.82547\n",
+            "Loss after epoch 11000 is 18.78368\n",
+            "Loss after epoch 11050 is 18.74198\n",
+            "Loss after epoch 11100 is 18.700365\n",
+            "Loss after epoch 11150 is 18.658863\n",
+            "Loss after epoch 11200 is 18.617468\n",
+            "Loss after epoch 11250 is 18.576172\n",
+            "Loss after epoch 11300 is 18.534956\n",
+            "Loss after epoch 11350 is 18.49383\n",
+            "Loss after epoch 11400 is 18.452805\n",
+            "Loss after epoch 11450 is 18.411915\n",
+            "Loss after epoch 11500 is 18.371086\n",
+            "Loss after epoch 11550 is 18.330326\n",
+            "Loss after epoch 11600 is 18.28971\n",
+            "Loss after epoch 11650 is 18.24917\n",
+            "Loss after epoch 11700 is 18.208706\n",
+            "Loss after epoch 11750 is 18.168377\n",
+            "Loss after epoch 11800 is 18.128109\n",
+            "Loss after epoch 11850 is 18.087954\n",
+            "Loss after epoch 11900 is 18.047867\n",
+            "Loss after epoch 11950 is 18.007902\n",
+            "Loss after epoch 12000 is 17.968018\n",
+            "Loss after epoch 12050 is 17.928207\n",
+            "Loss after epoch 12100 is 17.888535\n",
+            "Loss after epoch 12150 is 17.848907\n",
+            "Loss after epoch 12200 is 17.809418\n",
+            "Loss after epoch 12250 is 17.769987\n",
+            "Loss after epoch 12300 is 17.730663\n",
+            "Loss after epoch 12350 is 17.691427\n",
+            "Loss after epoch 12400 is 17.652294\n",
+            "Loss after epoch 12450 is 17.613249\n",
+            "Loss after epoch 12500 is 17.574286\n",
+            "Loss after epoch 12550 is 17.535397\n",
+            "Loss after epoch 12600 is 17.496634\n",
+            "Loss after epoch 12650 is 17.457943\n",
+            "Loss after epoch 12700 is 17.419367\n",
+            "Loss after epoch 12750 is 17.380846\n",
+            "Loss after epoch 12800 is 17.34243\n",
+            "Loss after epoch 12850 is 17.304092\n",
+            "Loss after epoch 12900 is 17.26589\n",
+            "Loss after epoch 12950 is 17.227737\n",
+            "Loss after epoch 13000 is 17.189651\n",
+            "Loss after epoch 13050 is 17.151703\n",
+            "Loss after epoch 13100 is 17.113834\n",
+            "Loss after epoch 13150 is 17.076015\n",
+            "Loss after epoch 13200 is 17.038324\n",
+            "Loss after epoch 13250 is 17.000708\n",
+            "Loss after epoch 13300 is 16.963184\n",
+            "Loss after epoch 13350 is 16.925734\n",
+            "Loss after epoch 13400 is 16.888412\n",
+            "Loss after epoch 13450 is 16.851141\n",
+            "Loss after epoch 13500 is 16.813946\n",
+            "Loss after epoch 13550 is 16.776884\n",
+            "Loss after epoch 13600 is 16.73988\n",
+            "Loss after epoch 13650 is 16.702932\n",
+            "Loss after epoch 13700 is 16.666113\n",
+            "Loss after epoch 13750 is 16.629374\n",
+            "Loss after epoch 13800 is 16.592718\n",
+            "Loss after epoch 13850 is 16.556133\n",
+            "Loss after epoch 13900 is 16.51966\n",
+            "Loss after epoch 13950 is 16.48327\n",
+            "Loss after epoch 14000 is 16.446941\n",
+            "Loss after epoch 14050 is 16.410725\n",
+            "Loss after epoch 14100 is 16.374563\n",
+            "Loss after epoch 14150 is 16.338484\n",
+            "Loss after epoch 14200 is 16.302523\n",
+            "Loss after epoch 14250 is 16.266626\n",
+            "Loss after epoch 14300 is 16.230812\n",
+            "Loss after epoch 14350 is 16.195078\n",
+            "Loss after epoch 14400 is 16.159466\n",
+            "Loss after epoch 14450 is 16.123903\n",
+            "Loss after epoch 14500 is 16.088398\n",
+            "Loss after epoch 14550 is 16.053022\n",
+            "Loss after epoch 14600 is 16.017712\n",
+            "Loss after epoch 14650 is 15.982489\n",
+            "Loss after epoch 14700 is 15.947325\n",
+            "Loss after epoch 14750 is 15.912292\n",
+            "Loss after epoch 14800 is 15.877283\n",
+            "Loss after epoch 14850 is 15.8424\n",
+            "Loss after epoch 14900 is 15.8075905\n",
+            "Loss after epoch 14950 is 15.772859\n",
+            "Loss after epoch 15000 is 15.738182\n",
+            "Loss after epoch 15050 is 15.70362\n",
+            "Loss after epoch 15100 is 15.66912\n",
+            "Loss after epoch 15150 is 15.634707\n",
+            "Loss after epoch 15200 is 15.600397\n",
+            "Loss after epoch 15250 is 15.566124\n",
+            "Loss after epoch 15300 is 15.531951\n",
+            "Loss after epoch 15350 is 15.497876\n",
+            "Loss after epoch 15400 is 15.463857\n",
+            "Loss after epoch 15450 is 15.429902\n",
+            "Loss after epoch 15500 is 15.396054\n",
+            "Loss after epoch 15550 is 15.362298\n",
+            "Loss after epoch 15600 is 15.328601\n",
+            "Loss after epoch 15650 is 15.2949705\n",
+            "Loss after epoch 15700 is 15.261448\n",
+            "Loss after epoch 15750 is 15.227977\n",
+            "Loss after epoch 15800 is 15.194621\n",
+            "Loss after epoch 15850 is 15.161318\n",
+            "Loss after epoch 15900 is 15.128081\n",
+            "Loss after epoch 15950 is 15.094921\n",
+            "Loss after epoch 16000 is 15.061883\n",
+            "Loss after epoch 16050 is 15.02886\n",
+            "Loss after epoch 16100 is 14.995965\n",
+            "Loss after epoch 16150 is 14.963125\n",
+            "Loss after epoch 16200 is 14.930357\n",
+            "Loss after epoch 16250 is 14.897694\n",
+            "Loss after epoch 16300 is 14.865076\n",
+            "Loss after epoch 16350 is 14.832541\n",
+            "Loss after epoch 16400 is 14.80008\n",
+            "Loss after epoch 16450 is 14.767705\n",
+            "Loss after epoch 16500 is 14.735389\n",
+            "Loss after epoch 16550 is 14.703162\n",
+            "Loss after epoch 16600 is 14.671025\n",
+            "Loss after epoch 16650 is 14.63893\n",
+            "Loss after epoch 16700 is 14.60696\n",
+            "Loss after epoch 16750 is 14.574993\n",
+            "Loss after epoch 16800 is 14.543155\n",
+            "Loss after epoch 16850 is 14.511386\n",
+            "Loss after epoch 16900 is 14.479678\n",
+            "Loss after epoch 16950 is 14.448046\n",
+            "Loss after epoch 17000 is 14.416486\n",
+            "Loss after epoch 17050 is 14.385028\n",
+            "Loss after epoch 17100 is 14.353585\n",
+            "Loss after epoch 17150 is 14.322271\n",
+            "Loss after epoch 17200 is 14.290994\n",
+            "Loss after epoch 17250 is 14.259812\n",
+            "Loss after epoch 17300 is 14.22869\n",
+            "Loss after epoch 17350 is 14.197662\n",
+            "Loss after epoch 17400 is 14.166688\n",
+            "Loss after epoch 17450 is 14.135789\n",
+            "Loss after epoch 17500 is 14.104978\n",
+            "Loss after epoch 17550 is 14.074213\n",
+            "Loss after epoch 17600 is 14.043513\n",
+            "Loss after epoch 17650 is 14.012924\n",
+            "Loss after epoch 17700 is 13.982389\n",
+            "Loss after epoch 17750 is 13.951915\n",
+            "Loss after epoch 17800 is 13.921518\n",
+            "Loss after epoch 17850 is 13.891195\n",
+            "Loss after epoch 17900 is 13.860926\n",
+            "Loss after epoch 17950 is 13.830767\n",
+            "Loss after epoch 18000 is 13.800663\n",
+            "Loss after epoch 18050 is 13.770593\n",
+            "Loss after epoch 18100 is 13.740626\n",
+            "Loss after epoch 18150 is 13.710727\n",
+            "Loss after epoch 18200 is 13.680901\n",
+            "Loss after epoch 18250 is 13.651115\n",
+            "Loss after epoch 18300 is 13.621448\n",
+            "Loss after epoch 18350 is 13.5918255\n",
+            "Loss after epoch 18400 is 13.562273\n",
+            "Loss after epoch 18450 is 13.532782\n",
+            "Loss after epoch 18500 is 13.503359\n",
+            "Loss after epoch 18550 is 13.474033\n",
+            "Loss after epoch 18600 is 13.444732\n",
+            "Loss after epoch 18650 is 13.415551\n",
+            "Loss after epoch 18700 is 13.386387\n",
+            "Loss after epoch 18750 is 13.357317\n",
+            "Loss after epoch 18800 is 13.328334\n",
+            "Loss after epoch 18850 is 13.29938\n",
+            "Loss after epoch 18900 is 13.270507\n",
+            "Loss after epoch 18950 is 13.241714\n",
+            "Loss after epoch 19000 is 13.212977\n",
+            "Loss after epoch 19050 is 13.184304\n",
+            "Loss after epoch 19100 is 13.155708\n",
+            "Loss after epoch 19150 is 13.1271715\n",
+            "Loss after epoch 19200 is 13.098717\n",
+            "Loss after epoch 19250 is 13.07031\n",
+            "Loss after epoch 19300 is 13.041971\n",
+            "Loss after epoch 19350 is 13.013712\n",
+            "Loss after epoch 19400 is 12.985503\n",
+            "Loss after epoch 19450 is 12.957357\n",
+            "Loss after epoch 19500 is 12.929307\n",
+            "Loss after epoch 19550 is 12.901297\n",
+            "Loss after epoch 19600 is 12.873368\n",
+            "Loss after epoch 19650 is 12.845476\n",
+            "Loss after epoch 19700 is 12.817679\n",
+            "Loss after epoch 19750 is 12.78995\n",
+            "Loss after epoch 19800 is 12.762254\n",
+            "Loss after epoch 19850 is 12.734644\n",
+            "Loss after epoch 19900 is 12.707098\n",
+            "Loss after epoch 19950 is 12.67961\n",
+            "Loss after epoch 20000 is 12.652191\n",
+            "Loss after epoch 20050 is 12.624826\n",
+            "Loss after epoch 20100 is 12.597537\n",
+            "Loss after epoch 20150 is 12.570316\n",
+            "Loss after epoch 20200 is 12.54315\n",
+            "Loss after epoch 20250 is 12.516038\n",
+            "Loss after epoch 20300 is 12.489014\n",
+            "Loss after epoch 20350 is 12.462041\n",
+            "Loss after epoch 20400 is 12.435125\n",
+            "Loss after epoch 20450 is 12.408282\n",
+            "Loss after epoch 20500 is 12.381498\n",
+            "Loss after epoch 20550 is 12.354787\n",
+            "Loss after epoch 20600 is 12.328113\n",
+            "Loss after epoch 20650 is 12.301514\n",
+            "Loss after epoch 20700 is 12.274984\n",
+            "Loss after epoch 20750 is 12.248499\n",
+            "Loss after epoch 20800 is 12.222095\n",
+            "Loss after epoch 20850 is 12.19575\n",
+            "Loss after epoch 20900 is 12.169474\n",
+            "Loss after epoch 20950 is 12.143227\n",
+            "Loss after epoch 21000 is 12.117057\n",
+            "Loss after epoch 21050 is 12.090978\n",
+            "Loss after epoch 21100 is 12.064907\n",
+            "Loss after epoch 21150 is 12.038944\n",
+            "Loss after epoch 21200 is 12.013016\n",
+            "Loss after epoch 21250 is 11.987155\n",
+            "Loss after epoch 21300 is 11.961358\n",
+            "Loss after epoch 21350 is 11.935624\n",
+            "Loss after epoch 21400 is 11.909937\n",
+            "Loss after epoch 21450 is 11.884318\n",
+            "Loss after epoch 21500 is 11.858761\n",
+            "Loss after epoch 21550 is 11.833258\n",
+            "Loss after epoch 21600 is 11.807829\n",
+            "Loss after epoch 21650 is 11.782439\n",
+            "Loss after epoch 21700 is 11.75711\n",
+            "Loss after epoch 21750 is 11.731853\n",
+            "Loss after epoch 21800 is 11.706639\n",
+            "Loss after epoch 21850 is 11.6815\n",
+            "Loss after epoch 21900 is 11.656418\n",
+            "Loss after epoch 21950 is 11.631406\n",
+            "Loss after epoch 22000 is 11.60643\n",
+            "Loss after epoch 22050 is 11.581513\n",
+            "Loss after epoch 22100 is 11.556664\n",
+            "Loss after epoch 22150 is 11.531861\n",
+            "Loss after epoch 22200 is 11.507136\n",
+            "Loss after epoch 22250 is 11.482459\n",
+            "Loss after epoch 22300 is 11.45784\n",
+            "Loss after epoch 22350 is 11.433269\n",
+            "Loss after epoch 22400 is 11.408786\n",
+            "Loss after epoch 22450 is 11.384321\n",
+            "Loss after epoch 22500 is 11.359944\n",
+            "Loss after epoch 22550 is 11.335596\n",
+            "Loss after epoch 22600 is 11.311334\n",
+            "Loss after epoch 22650 is 11.287108\n",
+            "Loss after epoch 22700 is 11.262945\n",
+            "Loss after epoch 22750 is 11.238826\n",
+            "Loss after epoch 22800 is 11.214789\n",
+            "Loss after epoch 22850 is 11.19079\n",
+            "Loss after epoch 22900 is 11.166859\n",
+            "Loss after epoch 22950 is 11.1429825\n",
+            "Loss after epoch 23000 is 11.11915\n",
+            "Loss after epoch 23050 is 11.095371\n",
+            "Loss after epoch 23100 is 11.071653\n",
+            "Loss after epoch 23150 is 11.048008\n",
+            "Loss after epoch 23200 is 11.02439\n",
+            "Loss after epoch 23250 is 11.000854\n",
+            "Loss after epoch 23300 is 10.977373\n",
+            "Loss after epoch 23350 is 10.953935\n",
+            "Loss after epoch 23400 is 10.930542\n",
+            "Loss after epoch 23450 is 10.907206\n",
+            "Loss after epoch 23500 is 10.88392\n",
+            "Loss after epoch 23550 is 10.860719\n",
+            "Loss after epoch 23600 is 10.837551\n",
+            "Loss after epoch 23650 is 10.814441\n",
+            "Loss after epoch 23700 is 10.791376\n",
+            "Loss after epoch 23750 is 10.768373\n",
+            "Loss after epoch 23800 is 10.745437\n",
+            "Loss after epoch 23850 is 10.722532\n",
+            "Loss after epoch 23900 is 10.699682\n",
+            "Loss after epoch 23950 is 10.676897\n",
+            "Loss after epoch 24000 is 10.654165\n",
+            "Loss after epoch 24050 is 10.631478\n",
+            "Loss after epoch 24100 is 10.608868\n",
+            "Loss after epoch 24150 is 10.58629\n",
+            "Loss after epoch 24200 is 10.563748\n",
+            "Loss after epoch 24250 is 10.541279\n",
+            "Loss after epoch 24300 is 10.518868\n",
+            "Loss after epoch 24350 is 10.496495\n",
+            "Loss after epoch 24400 is 10.474187\n",
+            "Loss after epoch 24450 is 10.451936\n",
+            "Loss after epoch 24500 is 10.429711\n",
+            "Loss after epoch 24550 is 10.407563\n",
+            "Loss after epoch 24600 is 10.385486\n",
+            "Loss after epoch 24650 is 10.363434\n",
+            "Loss after epoch 24700 is 10.341401\n",
+            "Loss after epoch 24750 is 10.3194685\n",
+            "Loss after epoch 24800 is 10.297583\n",
+            "Loss after epoch 24850 is 10.275717\n",
+            "Loss after epoch 24900 is 10.253924\n",
+            "Loss after epoch 24950 is 10.232199\n",
+            "Loss after epoch 25000 is 10.210495\n",
+            "Loss after epoch 25050 is 10.188816\n",
+            "Loss after epoch 25100 is 10.167245\n",
+            "Loss after epoch 25150 is 10.145696\n",
+            "Loss after epoch 25200 is 10.124197\n",
+            "Loss after epoch 25250 is 10.102767\n",
+            "Loss after epoch 25300 is 10.081382\n",
+            "Loss after epoch 25350 is 10.0600395\n",
+            "Loss after epoch 25400 is 10.038715\n",
+            "Loss after epoch 25450 is 10.017504\n",
+            "Loss after epoch 25500 is 9.996319\n",
+            "Loss after epoch 25550 is 9.975131\n",
+            "Loss after epoch 25600 is 9.954072\n",
+            "Loss after epoch 25650 is 9.933038\n",
+            "Loss after epoch 25700 is 9.912033\n",
+            "Loss after epoch 25750 is 9.89105\n",
+            "Loss after epoch 25800 is 9.870189\n",
+            "Loss after epoch 25850 is 9.849344\n",
+            "Loss after epoch 25900 is 9.828514\n",
+            "Loss after epoch 25950 is 9.807768\n",
+            "Loss after epoch 26000 is 9.7870865\n",
+            "Loss after epoch 26050 is 9.766411\n",
+            "Loss after epoch 26100 is 9.7457905\n",
+            "Loss after epoch 26150 is 9.725269\n",
+            "Loss after epoch 26200 is 9.704766\n",
+            "Loss after epoch 26250 is 9.68426\n",
+            "Loss after epoch 26300 is 9.663864\n",
+            "Loss after epoch 26350 is 9.643516\n",
+            "Loss after epoch 26400 is 9.623191\n",
+            "Loss after epoch 26450 is 9.60291\n",
+            "Loss after epoch 26500 is 9.582707\n",
+            "Loss after epoch 26550 is 9.562528\n",
+            "Loss after epoch 26600 is 9.542373\n",
+            "Loss after epoch 26650 is 9.522298\n",
+            "Loss after epoch 26700 is 9.502292\n",
+            "Loss after epoch 26750 is 9.482284\n",
+            "Loss after epoch 26800 is 9.462328\n",
+            "Loss after epoch 26850 is 9.442464\n",
+            "Loss after epoch 26900 is 9.42261\n",
+            "Loss after epoch 26950 is 9.402796\n",
+            "Loss after epoch 27000 is 9.383052\n",
+            "Loss after epoch 27050 is 9.363337\n",
+            "Loss after epoch 27100 is 9.343674\n",
+            "Loss after epoch 27150 is 9.3240385\n",
+            "Loss after epoch 27200 is 9.3045\n",
+            "Loss after epoch 27250 is 9.284978\n",
+            "Loss after epoch 27300 is 9.265459\n",
+            "Loss after epoch 27350 is 9.246037\n",
+            "Loss after epoch 27400 is 9.226667\n",
+            "Loss after epoch 27450 is 9.20731\n",
+            "Loss after epoch 27500 is 9.188002\n",
+            "Loss after epoch 27550 is 9.168761\n",
+            "Loss after epoch 27600 is 9.149553\n",
+            "Loss after epoch 27650 is 9.130393\n",
+            "Loss after epoch 27700 is 9.11125\n",
+            "Loss after epoch 27750 is 9.092216\n",
+            "Loss after epoch 27800 is 9.073176\n",
+            "Loss after epoch 27850 is 9.054175\n",
+            "Loss after epoch 27900 is 9.035236\n",
+            "Loss after epoch 27950 is 9.016366\n",
+            "Loss after epoch 28000 is 8.997487\n",
+            "Loss after epoch 28050 is 8.978654\n",
+            "Loss after epoch 28100 is 8.959918\n",
+            "Loss after epoch 28150 is 8.941204\n",
+            "Loss after epoch 28200 is 8.922517\n",
+            "Loss after epoch 28250 is 8.90388\n",
+            "Loss after epoch 28300 is 8.8853035\n",
+            "Loss after epoch 28350 is 8.866778\n",
+            "Loss after epoch 28400 is 8.848248\n",
+            "Loss after epoch 28450 is 8.829806\n",
+            "Loss after epoch 28500 is 8.811398\n",
+            "Loss after epoch 28550 is 8.793029\n",
+            "Loss after epoch 28600 is 8.774666\n",
+            "Loss after epoch 28650 is 8.756402\n",
+            "Loss after epoch 28700 is 8.738178\n",
+            "Loss after epoch 28750 is 8.719954\n",
+            "Loss after epoch 28800 is 8.701778\n",
+            "Loss after epoch 28850 is 8.683698\n",
+            "Loss after epoch 28900 is 8.665628\n",
+            "Loss after epoch 28950 is 8.647567\n",
+            "Loss after epoch 29000 is 8.629582\n",
+            "Loss after epoch 29050 is 8.611648\n",
+            "Loss after epoch 29100 is 8.593737\n",
+            "Loss after epoch 29150 is 8.575847\n",
+            "Loss after epoch 29200 is 8.558047\n",
+            "Loss after epoch 29250 is 8.540276\n",
+            "Loss after epoch 29300 is 8.522545\n",
+            "Loss after epoch 29350 is 8.504813\n",
+            "Loss after epoch 29400 is 8.487195\n",
+            "Loss after epoch 29450 is 8.469581\n",
+            "Loss after epoch 29500 is 8.452001\n",
+            "Loss after epoch 29550 is 8.434448\n",
+            "Loss after epoch 29600 is 8.416979\n",
+            "Loss after epoch 29650 is 8.399543\n",
+            "Loss after epoch 29700 is 8.382095\n",
+            "Loss after epoch 29750 is 8.364733\n",
+            "Loss after epoch 29800 is 8.347425\n",
+            "Loss after epoch 29850 is 8.33014\n",
+            "Loss after epoch 29900 is 8.312872\n",
+            "Loss after epoch 29950 is 8.295671\n",
+            "Loss after epoch 30000 is 8.278532\n",
+            "Loss after epoch 30050 is 8.2613945\n",
+            "Loss after epoch 30100 is 8.244285\n",
+            "Loss after epoch 30150 is 8.227254\n",
+            "Loss after epoch 30200 is 8.210261\n",
+            "Loss after epoch 30250 is 8.1932955\n",
+            "Loss after epoch 30300 is 8.176337\n",
+            "Loss after epoch 30350 is 8.159472\n",
+            "Loss after epoch 30400 is 8.142633\n",
+            "Loss after epoch 30450 is 8.125817\n",
+            "Loss after epoch 30500 is 8.109024\n",
+            "Loss after epoch 30550 is 8.092329\n",
+            "Loss after epoch 30600 is 8.075648\n",
+            "Loss after epoch 30650 is 8.058966\n",
+            "Loss after epoch 30700 is 8.042343\n",
+            "Loss after epoch 30750 is 8.025792\n",
+            "Loss after epoch 30800 is 8.009261\n",
+            "Loss after epoch 30850 is 7.9927473\n",
+            "Loss after epoch 30900 is 7.976277\n",
+            "Loss after epoch 30950 is 7.959896\n",
+            "Loss after epoch 31000 is 7.943511\n",
+            "Loss after epoch 31050 is 7.927149\n",
+            "Loss after epoch 31100 is 7.9108343\n",
+            "Loss after epoch 31150 is 7.8945985\n",
+            "Loss after epoch 31200 is 7.878361\n",
+            "Loss after epoch 31250 is 7.862166\n",
+            "Loss after epoch 31300 is 7.8460073\n",
+            "Loss after epoch 31350 is 7.829913\n",
+            "Loss after epoch 31400 is 7.813847\n",
+            "Loss after epoch 31450 is 7.797772\n",
+            "Loss after epoch 31500 is 7.781781\n",
+            "Loss after epoch 31550 is 7.7658334\n",
+            "Loss after epoch 31600 is 7.7499156\n",
+            "Loss after epoch 31650 is 7.7340064\n",
+            "Loss after epoch 31700 is 7.7181425\n",
+            "Loss after epoch 31750 is 7.702341\n",
+            "Loss after epoch 31800 is 7.686581\n",
+            "Loss after epoch 31850 is 7.670816\n",
+            "Loss after epoch 31900 is 7.655113\n",
+            "Loss after epoch 31950 is 7.63946\n",
+            "Loss after epoch 32000 is 7.6238194\n",
+            "Loss after epoch 32050 is 7.608214\n",
+            "Loss after epoch 32100 is 7.5926523\n",
+            "Loss after epoch 32150 is 7.5771627\n",
+            "Loss after epoch 32200 is 7.5616703\n",
+            "Loss after epoch 32250 is 7.546203\n",
+            "Loss after epoch 32300 is 7.530787\n",
+            "Loss after epoch 32350 is 7.515424\n",
+            "Loss after epoch 32400 is 7.500089\n",
+            "Loss after epoch 32450 is 7.484774\n",
+            "Loss after epoch 32500 is 7.46949\n",
+            "Loss after epoch 32550 is 7.454277\n",
+            "Loss after epoch 32600 is 7.439078\n",
+            "Loss after epoch 32650 is 7.4238987\n",
+            "Loss after epoch 32700 is 7.4087687\n",
+            "Loss after epoch 32750 is 7.3936844\n",
+            "Loss after epoch 32800 is 7.3786526\n",
+            "Loss after epoch 32850 is 7.363611\n",
+            "Loss after epoch 32900 is 7.3486123\n",
+            "Loss after epoch 32950 is 7.333694\n",
+            "Loss after epoch 33000 is 7.3187737\n",
+            "Loss after epoch 33050 is 7.303889\n",
+            "Loss after epoch 33100 is 7.289013\n",
+            "Loss after epoch 33150 is 7.274236\n",
+            "Loss after epoch 33200 is 7.259452\n",
+            "Loss after epoch 33250 is 7.244708\n",
+            "Loss after epoch 33300 is 7.2299743\n",
+            "Loss after epoch 33350 is 7.215328\n",
+            "Loss after epoch 33400 is 7.200702\n",
+            "Loss after epoch 33450 is 7.186091\n",
+            "Loss after epoch 33500 is 7.1714983\n",
+            "Loss after epoch 33550 is 7.1569715\n",
+            "Loss after epoch 33600 is 7.1424823\n",
+            "Loss after epoch 33650 is 7.1280074\n",
+            "Loss after epoch 33700 is 7.113545\n",
+            "Loss after epoch 33750 is 7.0991607\n",
+            "Loss after epoch 33800 is 7.084801\n",
+            "Loss after epoch 33850 is 7.0704813\n",
+            "Loss after epoch 33900 is 7.056156\n",
+            "Loss after epoch 33950 is 7.0418897\n",
+            "Loss after epoch 34000 is 7.0276814\n",
+            "Loss after epoch 34050 is 7.013473\n",
+            "Loss after epoch 34100 is 6.9992933\n",
+            "Loss after epoch 34150 is 6.985146\n",
+            "Loss after epoch 34200 is 6.971066\n",
+            "Loss after epoch 34250 is 6.95701\n",
+            "Loss after epoch 34300 is 6.942967\n",
+            "Loss after epoch 34350 is 6.9289274\n",
+            "Loss after epoch 34400 is 6.914979\n",
+            "Loss after epoch 34450 is 6.901054\n",
+            "Loss after epoch 34500 is 6.887141\n",
+            "Loss after epoch 34550 is 6.8732486\n",
+            "Loss after epoch 34600 is 6.8594365\n",
+            "Loss after epoch 34650 is 6.845644\n",
+            "Loss after epoch 34700 is 6.8318567\n",
+            "Loss after epoch 34750 is 6.8181133\n",
+            "Loss after epoch 34800 is 6.8043885\n",
+            "Loss after epoch 34850 is 6.790734\n",
+            "Loss after epoch 34900 is 6.777083\n",
+            "Loss after epoch 34950 is 6.763464\n",
+            "Loss after epoch 35000 is 6.7498674\n",
+            "Loss after epoch 35050 is 6.736341\n",
+            "Loss after epoch 35100 is 6.7228174\n",
+            "Loss after epoch 35150 is 6.7093277\n",
+            "Loss after epoch 35200 is 6.6958494\n",
+            "Loss after epoch 35250 is 6.6824474\n",
+            "Loss after epoch 35300 is 6.669072\n",
+            "Loss after epoch 35350 is 6.6557093\n",
+            "Loss after epoch 35400 is 6.6423593\n",
+            "Loss after epoch 35450 is 6.629055\n",
+            "Loss after epoch 35500 is 6.6158056\n",
+            "Loss after epoch 35550 is 6.602567\n",
+            "Loss after epoch 35600 is 6.589341\n",
+            "Loss after epoch 35650 is 6.576157\n",
+            "Loss after epoch 35700 is 6.56305\n",
+            "Loss after epoch 35750 is 6.54993\n",
+            "Loss after epoch 35800 is 6.536834\n",
+            "Loss after epoch 35850 is 6.5237727\n",
+            "Loss after epoch 35900 is 6.510758\n",
+            "Loss after epoch 35950 is 6.497785\n",
+            "Loss after epoch 36000 is 6.484812\n",
+            "Loss after epoch 36050 is 6.471871\n",
+            "Loss after epoch 36100 is 6.458971\n",
+            "Loss after epoch 36150 is 6.446119\n",
+            "Loss after epoch 36200 is 6.4332905\n",
+            "Loss after epoch 36250 is 6.420462\n",
+            "Loss after epoch 36300 is 6.4076543\n",
+            "Loss after epoch 36350 is 6.39493\n",
+            "Loss after epoch 36400 is 6.382219\n",
+            "Loss after epoch 36450 is 6.369523\n",
+            "Loss after epoch 36500 is 6.3568425\n",
+            "Loss after epoch 36550 is 6.3442206\n",
+            "Loss after epoch 36600 is 6.3316355\n",
+            "Loss after epoch 36650 is 6.319064\n",
+            "Loss after epoch 36700 is 6.306503\n",
+            "Loss after epoch 36750 is 6.2939878\n",
+            "Loss after epoch 36800 is 6.281519\n",
+            "Loss after epoch 36850 is 6.2690606\n",
+            "Loss after epoch 36900 is 6.25664\n",
+            "Loss after epoch 36950 is 6.2442183\n",
+            "Loss after epoch 37000 is 6.231861\n",
+            "Loss after epoch 37050 is 6.219538\n",
+            "Loss after epoch 37100 is 6.207241\n",
+            "Loss after epoch 37150 is 6.194936\n",
+            "Loss after epoch 37200 is 6.1826687\n",
+            "Loss after epoch 37250 is 6.170473\n",
+            "Loss after epoch 37300 is 6.158289\n",
+            "Loss after epoch 37350 is 6.146099\n",
+            "Loss after epoch 37400 is 6.133947\n",
+            "Loss after epoch 37450 is 6.12185\n",
+            "Loss after epoch 37500 is 6.10978\n",
+            "Loss after epoch 37550 is 6.097728\n",
+            "Loss after epoch 37600 is 6.085694\n",
+            "Loss after epoch 37650 is 6.0736694\n",
+            "Loss after epoch 37700 is 6.0617213\n",
+            "Loss after epoch 37750 is 6.049802\n",
+            "Loss after epoch 37800 is 6.037884\n",
+            "Loss after epoch 37850 is 6.025973\n",
+            "Loss after epoch 37900 is 6.014111\n",
+            "Loss after epoch 37950 is 6.002307\n",
+            "Loss after epoch 38000 is 5.990502\n",
+            "Loss after epoch 38050 is 5.978728\n",
+            "Loss after epoch 38100 is 5.9669485\n",
+            "Loss after epoch 38150 is 5.9552464\n",
+            "Loss after epoch 38200 is 5.9435773\n",
+            "Loss after epoch 38250 is 5.931912\n",
+            "Loss after epoch 38300 is 5.920269\n",
+            "Loss after epoch 38350 is 5.908628\n",
+            "Loss after epoch 38400 is 5.897071\n",
+            "Loss after epoch 38450 is 5.8855247\n",
+            "Loss after epoch 38500 is 5.873994\n",
+            "Loss after epoch 38550 is 5.862472\n",
+            "Loss after epoch 38600 is 5.851006\n",
+            "Loss after epoch 38650 is 5.8395667\n",
+            "Loss after epoch 38700 is 5.828153\n",
+            "Loss after epoch 38750 is 5.8167434\n",
+            "Loss after epoch 38800 is 5.805351\n",
+            "Loss after epoch 38850 is 5.794033\n",
+            "Loss after epoch 38900 is 5.7827215\n",
+            "Loss after epoch 38950 is 5.7714443\n",
+            "Loss after epoch 39000 is 5.760165\n",
+            "Loss after epoch 39050 is 5.748919\n",
+            "Loss after epoch 39100 is 5.737723\n",
+            "Loss after epoch 39150 is 5.7265515\n",
+            "Loss after epoch 39200 is 5.7153926\n",
+            "Loss after epoch 39250 is 5.7042456\n",
+            "Loss after epoch 39300 is 5.6931334\n",
+            "Loss after epoch 39350 is 5.6820674\n",
+            "Loss after epoch 39400 is 5.6710277\n",
+            "Loss after epoch 39450 is 5.6599975\n",
+            "Loss after epoch 39500 is 5.6489773\n",
+            "Loss after epoch 39550 is 5.6379986\n",
+            "Loss after epoch 39600 is 5.6270638\n",
+            "Loss after epoch 39650 is 5.6161437\n",
+            "Loss after epoch 39700 is 5.605234\n",
+            "Loss after epoch 39750 is 5.594359\n",
+            "Loss after epoch 39800 is 5.583513\n",
+            "Loss after epoch 39850 is 5.5727015\n",
+            "Loss after epoch 39900 is 5.5619187\n",
+            "Loss after epoch 39950 is 5.5511293\n",
+            "Loss after epoch 40000 is 5.5403595\n",
+            "Loss after epoch 40050 is 5.5296636\n",
+            "Loss after epoch 40100 is 5.5189734\n",
+            "Loss after epoch 40150 is 5.50831\n",
+            "Loss after epoch 40200 is 5.4976435\n",
+            "Loss after epoch 40250 is 5.4870124\n",
+            "Loss after epoch 40300 is 5.4764233\n",
+            "Loss after epoch 40350 is 5.465869\n",
+            "Loss after epoch 40400 is 5.4553204\n",
+            "Loss after epoch 40450 is 5.4447737\n",
+            "Loss after epoch 40500 is 5.434271\n",
+            "Loss after epoch 40550 is 5.4238167\n",
+            "Loss after epoch 40600 is 5.413378\n",
+            "Loss after epoch 40650 is 5.4029517\n",
+            "Loss after epoch 40700 is 5.3925357\n",
+            "Loss after epoch 40750 is 5.3821487\n",
+            "Loss after epoch 40800 is 5.3718243\n",
+            "Loss after epoch 40850 is 5.3615\n",
+            "Loss after epoch 40900 is 5.351192\n",
+            "Loss after epoch 40950 is 5.3408957\n",
+            "Loss after epoch 41000 is 5.3306355\n",
+            "Loss after epoch 41050 is 5.320417\n",
+            "Loss after epoch 41100 is 5.3102283\n",
+            "Loss after epoch 41150 is 5.3000364\n",
+            "Loss after epoch 41200 is 5.2898607\n",
+            "Loss after epoch 41250 is 5.27973\n",
+            "Loss after epoch 41300 is 5.269627\n",
+            "Loss after epoch 41350 is 5.259549\n",
+            "Loss after epoch 41400 is 5.249473\n",
+            "Loss after epoch 41450 is 5.2394214\n",
+            "Loss after epoch 41500 is 5.229395\n",
+            "Loss after epoch 41550 is 5.219424\n",
+            "Loss after epoch 41600 is 5.2094607\n",
+            "Loss after epoch 41650 is 5.1995144\n",
+            "Loss after epoch 41700 is 5.189558\n",
+            "Loss after epoch 41750 is 5.1796594\n",
+            "Loss after epoch 41800 is 5.169802\n",
+            "Loss after epoch 41850 is 5.159956\n",
+            "Loss after epoch 41900 is 5.15012\n",
+            "Loss after epoch 41950 is 5.140296\n",
+            "Loss after epoch 42000 is 5.130499\n",
+            "Loss after epoch 42050 is 5.120755\n",
+            "Loss after epoch 42100 is 5.1110187\n",
+            "Loss after epoch 42150 is 5.1013103\n",
+            "Loss after epoch 42200 is 5.0915947\n",
+            "Loss after epoch 42250 is 5.0819106\n",
+            "Loss after epoch 42300 is 5.072277\n",
+            "Loss after epoch 42350 is 5.0626636\n",
+            "Loss after epoch 42400 is 5.053055\n",
+            "Loss after epoch 42450 is 5.0434656\n",
+            "Loss after epoch 42500 is 5.0338855\n",
+            "Loss after epoch 42550 is 5.0243716\n",
+            "Loss after epoch 42600 is 5.0148754\n",
+            "Loss after epoch 42650 is 5.0053706\n",
+            "Loss after epoch 42700 is 4.9958925\n",
+            "Loss after epoch 42750 is 4.9864287\n",
+            "Loss after epoch 42800 is 4.977026\n",
+            "Loss after epoch 42850 is 4.9676194\n",
+            "Loss after epoch 42900 is 4.958237\n",
+            "Loss after epoch 42950 is 4.94887\n",
+            "Loss after epoch 43000 is 4.9395165\n",
+            "Loss after epoch 43050 is 4.9302077\n",
+            "Loss after epoch 43100 is 4.920943\n",
+            "Loss after epoch 43150 is 4.9116707\n",
+            "Loss after epoch 43200 is 4.9024096\n",
+            "Loss after epoch 43250 is 4.8931603\n",
+            "Loss after epoch 43300 is 4.8839593\n",
+            "Loss after epoch 43350 is 4.874786\n",
+            "Loss after epoch 43400 is 4.8656197\n",
+            "Loss after epoch 43450 is 4.856484\n",
+            "Loss after epoch 43500 is 4.8473415\n",
+            "Loss after epoch 43550 is 4.8382344\n",
+            "Loss after epoch 43600 is 4.8291783\n",
+            "Loss after epoch 43650 is 4.8201203\n",
+            "Loss after epoch 43700 is 4.811085\n",
+            "Loss after epoch 43750 is 4.802051\n",
+            "Loss after epoch 43800 is 4.793043\n",
+            "Loss after epoch 43850 is 4.7840962\n",
+            "Loss after epoch 43900 is 4.7751417\n",
+            "Loss after epoch 43950 is 4.7662163\n",
+            "Loss after epoch 44000 is 4.757295\n",
+            "Loss after epoch 44050 is 4.74839\n",
+            "Loss after epoch 44100 is 4.739529\n",
+            "Loss after epoch 44150 is 4.730694\n",
+            "Loss after epoch 44200 is 4.7218733\n",
+            "Loss after epoch 44250 is 4.7130585\n",
+            "Loss after epoch 44300 is 4.7042527\n",
+            "Loss after epoch 44350 is 4.6954947\n",
+            "Loss after epoch 44400 is 4.686761\n",
+            "Loss after epoch 44450 is 4.6780453\n",
+            "Loss after epoch 44500 is 4.6693335\n",
+            "Loss after epoch 44550 is 4.660631\n",
+            "Loss after epoch 44600 is 4.6519604\n",
+            "Loss after epoch 44650 is 4.643334\n",
+            "Loss after epoch 44700 is 4.634729\n",
+            "Loss after epoch 44750 is 4.626118\n",
+            "Loss after epoch 44800 is 4.6175213\n",
+            "Loss after epoch 44850 is 4.608947\n",
+            "Loss after epoch 44900 is 4.600414\n",
+            "Loss after epoch 44950 is 4.591895\n",
+            "Loss after epoch 45000 is 4.583406\n",
+            "Loss after epoch 45050 is 4.5749216\n",
+            "Loss after epoch 45100 is 4.566434\n",
+            "Loss after epoch 45150 is 4.557984\n",
+            "Loss after epoch 45200 is 4.5495834\n",
+            "Loss after epoch 45250 is 4.5411925\n",
+            "Loss after epoch 45300 is 4.5327992\n",
+            "Loss after epoch 45350 is 4.5244207\n",
+            "Loss after epoch 45400 is 4.5160594\n",
+            "Loss after epoch 45450 is 4.507754\n",
+            "Loss after epoch 45500 is 4.4994583\n",
+            "Loss after epoch 45550 is 4.491178\n",
+            "Loss after epoch 45600 is 4.4829006\n",
+            "Loss after epoch 45650 is 4.4746375\n",
+            "Loss after epoch 45700 is 4.4663954\n",
+            "Loss after epoch 45750 is 4.4582067\n",
+            "Loss after epoch 45800 is 4.450019\n",
+            "Loss after epoch 45850 is 4.4418554\n",
+            "Loss after epoch 45900 is 4.4336944\n",
+            "Loss after epoch 45950 is 4.425536\n",
+            "Loss after epoch 46000 is 4.4174347\n",
+            "Loss after epoch 46050 is 4.409361\n",
+            "Loss after epoch 46100 is 4.401283\n",
+            "Loss after epoch 46150 is 4.393225\n",
+            "Loss after epoch 46200 is 4.3851695\n",
+            "Loss after epoch 46250 is 4.3771367\n",
+            "Loss after epoch 46300 is 4.369162\n",
+            "Loss after epoch 46350 is 4.3611794\n",
+            "Loss after epoch 46400 is 4.3532248\n",
+            "Loss after epoch 46450 is 4.34527\n",
+            "Loss after epoch 46500 is 4.3373346\n",
+            "Loss after epoch 46550 is 4.329418\n",
+            "Loss after epoch 46600 is 4.321548\n",
+            "Loss after epoch 46650 is 4.3136845\n",
+            "Loss after epoch 46700 is 4.305833\n",
+            "Loss after epoch 46750 is 4.2979856\n",
+            "Loss after epoch 46800 is 4.290157\n",
+            "Loss after epoch 46850 is 4.282368\n",
+            "Loss after epoch 46900 is 4.2746058\n",
+            "Loss after epoch 46950 is 4.2668395\n",
+            "Loss after epoch 47000 is 4.2591057\n",
+            "Loss after epoch 47050 is 4.2513623\n",
+            "Loss after epoch 47100 is 4.243639\n",
+            "Loss after epoch 47150 is 4.2359667\n",
+            "Loss after epoch 47200 is 4.2283144\n",
+            "Loss after epoch 47250 is 4.2206597\n",
+            "Loss after epoch 47300 is 4.213019\n",
+            "Loss after epoch 47350 is 4.2053847\n",
+            "Loss after epoch 47400 is 4.197782\n",
+            "Loss after epoch 47450 is 4.190225\n",
+            "Loss after epoch 47500 is 4.1826615\n",
+            "Loss after epoch 47550 is 4.175118\n",
+            "Loss after epoch 47600 is 4.167579\n",
+            "Loss after epoch 47650 is 4.160053\n",
+            "Loss after epoch 47700 is 4.1525626\n",
+            "Loss after epoch 47750 is 4.1451054\n",
+            "Loss after epoch 47800 is 4.137654\n",
+            "Loss after epoch 47850 is 4.130212\n",
+            "Loss after epoch 47900 is 4.122782\n",
+            "Loss after epoch 47950 is 4.1153445\n",
+            "Loss after epoch 48000 is 4.107983\n",
+            "Loss after epoch 48050 is 4.100624\n",
+            "Loss after epoch 48100 is 4.093271\n",
+            "Loss after epoch 48150 is 4.0859313\n",
+            "Loss after epoch 48200 is 4.078599\n",
+            "Loss after epoch 48250 is 4.0712757\n",
+            "Loss after epoch 48300 is 4.0640044\n",
+            "Loss after epoch 48350 is 4.056761\n",
+            "Loss after epoch 48400 is 4.0495076\n",
+            "Loss after epoch 48450 is 4.042268\n",
+            "Loss after epoch 48500 is 4.0350304\n",
+            "Loss after epoch 48550 is 4.0278254\n",
+            "Loss after epoch 48600 is 4.020656\n",
+            "Loss after epoch 48650 is 4.0135055\n",
+            "Loss after epoch 48700 is 4.006352\n",
+            "Loss after epoch 48750 is 3.999221\n",
+            "Loss after epoch 48800 is 3.992085\n",
+            "Loss after epoch 48850 is 3.9849706\n",
+            "Loss after epoch 48900 is 3.9779043\n",
+            "Loss after epoch 48950 is 3.9708493\n",
+            "Loss after epoch 49000 is 3.9638073\n",
+            "Loss after epoch 49050 is 3.956756\n",
+            "Loss after epoch 49100 is 3.9497316\n",
+            "Loss after epoch 49150 is 3.9427223\n",
+            "Loss after epoch 49200 is 3.9357584\n",
+            "Loss after epoch 49250 is 3.9288023\n",
+            "Loss after epoch 49300 is 3.9218378\n",
+            "Loss after epoch 49350 is 3.914897\n",
+            "Loss after epoch 49400 is 3.9079638\n",
+            "Loss after epoch 49450 is 3.9010508\n",
+            "Loss after epoch 49500 is 3.8941777\n",
+            "Loss after epoch 49550 is 3.887318\n",
+            "Loss after epoch 49600 is 3.8804762\n",
+            "Loss after epoch 49650 is 3.8736296\n",
+            "Loss after epoch 49700 is 3.86679\n",
+            "Loss after epoch 49750 is 3.859968\n",
+            "Loss after epoch 49800 is 3.8531907\n",
+            "Loss after epoch 49850 is 3.8464336\n",
+            "Loss after epoch 49900 is 3.8396757\n",
+            "Loss after epoch 49950 is 3.8329346\n",
+            "Loss after epoch 50000 is 3.826188\n",
+            "Loss after epoch 50050 is 3.819452\n",
+            "Loss after epoch 50100 is 3.8127787\n",
+            "Loss after epoch 50150 is 3.8061047\n",
+            "Loss after epoch 50200 is 3.7994502\n",
+            "Loss after epoch 50250 is 3.7928014\n",
+            "Loss after epoch 50300 is 3.786149\n",
+            "Loss after epoch 50350 is 3.7795148\n",
+            "Loss after epoch 50400 is 3.772928\n",
+            "Loss after epoch 50450 is 3.7663581\n",
+            "Loss after epoch 50500 is 3.7597787\n",
+            "Loss after epoch 50550 is 3.7532248\n",
+            "Loss after epoch 50600 is 3.7466762\n",
+            "Loss after epoch 50650 is 3.7401314\n",
+            "Loss after epoch 50700 is 3.7336287\n",
+            "Loss after epoch 50750 is 3.7271445\n",
+            "Loss after epoch 50800 is 3.720672\n",
+            "Loss after epoch 50850 is 3.7142055\n",
+            "Loss after epoch 50900 is 3.7077487\n",
+            "Loss after epoch 50950 is 3.7012937\n",
+            "Loss after epoch 51000 is 3.6948748\n",
+            "Loss after epoch 51050 is 3.6884868\n",
+            "Loss after epoch 51100 is 3.6821003\n",
+            "Loss after epoch 51150 is 3.6757364\n",
+            "Loss after epoch 51200 is 3.669365\n",
+            "Loss after epoch 51250 is 3.6630075\n",
+            "Loss after epoch 51300 is 3.6566591\n",
+            "Loss after epoch 51350 is 3.6503675\n",
+            "Loss after epoch 51400 is 3.6440728\n",
+            "Loss after epoch 51450 is 3.6377995\n",
+            "Loss after epoch 51500 is 3.631519\n",
+            "Loss after epoch 51550 is 3.6252565\n",
+            "Loss after epoch 51600 is 3.61899\n",
+            "Loss after epoch 51650 is 3.612775\n",
+            "Loss after epoch 51700 is 3.6065822\n",
+            "Loss after epoch 51750 is 3.60038\n",
+            "Loss after epoch 51800 is 3.5942025\n",
+            "Loss after epoch 51850 is 3.5880246\n",
+            "Loss after epoch 51900 is 3.5818448\n",
+            "Loss after epoch 51950 is 3.5757139\n",
+            "Loss after epoch 52000 is 3.5696058\n",
+            "Loss after epoch 52050 is 3.5635028\n",
+            "Loss after epoch 52100 is 3.5573943\n",
+            "Loss after epoch 52150 is 3.5513074\n",
+            "Loss after epoch 52200 is 3.545228\n",
+            "Loss after epoch 52250 is 3.5391545\n",
+            "Loss after epoch 52300 is 3.53313\n",
+            "Loss after epoch 52350 is 3.527113\n",
+            "Loss after epoch 52400 is 3.5211177\n",
+            "Loss after epoch 52450 is 3.5151153\n",
+            "Loss after epoch 52500 is 3.509117\n",
+            "Loss after epoch 52550 is 3.50313\n",
+            "Loss after epoch 52600 is 3.4971805\n",
+            "Loss after epoch 52650 is 3.4912496\n",
+            "Loss after epoch 52700 is 3.4853241\n",
+            "Loss after epoch 52750 is 3.4794202\n",
+            "Loss after epoch 52800 is 3.473507\n",
+            "Loss after epoch 52850 is 3.467606\n",
+            "Loss after epoch 52900 is 3.4617238\n",
+            "Loss after epoch 52950 is 3.4558768\n",
+            "Loss after epoch 53000 is 3.4500463\n",
+            "Loss after epoch 53050 is 3.4442122\n",
+            "Loss after epoch 53100 is 3.4383948\n",
+            "Loss after epoch 53150 is 3.4325755\n",
+            "Loss after epoch 53200 is 3.4267745\n",
+            "Loss after epoch 53250 is 3.4209945\n",
+            "Loss after epoch 53300 is 3.4152458\n",
+            "Loss after epoch 53350 is 3.4095082\n",
+            "Loss after epoch 53400 is 3.4037755\n",
+            "Loss after epoch 53450 is 3.398037\n",
+            "Loss after epoch 53500 is 3.392319\n",
+            "Loss after epoch 53550 is 3.386605\n",
+            "Loss after epoch 53600 is 3.3809319\n",
+            "Loss after epoch 53650 is 3.3752744\n",
+            "Loss after epoch 53700 is 3.3696232\n",
+            "Loss after epoch 53750 is 3.3639796\n",
+            "Loss after epoch 53800 is 3.358343\n",
+            "Loss after epoch 53850 is 3.3527122\n",
+            "Loss after epoch 53900 is 3.3470953\n",
+            "Loss after epoch 53950 is 3.3415217\n",
+            "Loss after epoch 54000 is 3.335949\n",
+            "Loss after epoch 54050 is 3.3303862\n",
+            "Loss after epoch 54100 is 3.3248417\n",
+            "Loss after epoch 54150 is 3.3192885\n",
+            "Loss after epoch 54200 is 3.3137465\n",
+            "Loss after epoch 54250 is 3.308233\n",
+            "Loss after epoch 54300 is 3.3027437\n",
+            "Loss after epoch 54350 is 3.2972693\n",
+            "Loss after epoch 54400 is 3.291793\n",
+            "Loss after epoch 54450 is 3.2863352\n",
+            "Loss after epoch 54500 is 3.280871\n",
+            "Loss after epoch 54550 is 3.2754228\n",
+            "Loss after epoch 54600 is 3.2700067\n",
+            "Loss after epoch 54650 is 3.2646015\n",
+            "Loss after epoch 54700 is 3.2592132\n",
+            "Loss after epoch 54750 is 3.2538278\n",
+            "Loss after epoch 54800 is 3.24845\n",
+            "Loss after epoch 54850 is 3.243079\n",
+            "Loss after epoch 54900 is 3.2377062\n",
+            "Loss after epoch 54950 is 3.2323837\n",
+            "Loss after epoch 55000 is 3.227075\n",
+            "Loss after epoch 55050 is 3.2217736\n",
+            "Loss after epoch 55100 is 3.2164776\n",
+            "Loss after epoch 55150 is 3.2111833\n",
+            "Loss after epoch 55200 is 3.2059\n",
+            "Loss after epoch 55250 is 3.200622\n",
+            "Loss after epoch 55300 is 3.1953893\n",
+            "Loss after epoch 55350 is 3.190163\n",
+            "Loss after epoch 55400 is 3.1849477\n",
+            "Loss after epoch 55450 is 3.1797345\n",
+            "Loss after epoch 55500 is 3.1745265\n",
+            "Loss after epoch 55550 is 3.169324\n",
+            "Loss after epoch 55600 is 3.1641288\n",
+            "Loss after epoch 55650 is 3.1589909\n",
+            "Loss after epoch 55700 is 3.153848\n",
+            "Loss after epoch 55750 is 3.148711\n",
+            "Loss after epoch 55800 is 3.1435897\n",
+            "Loss after epoch 55850 is 3.1384628\n",
+            "Loss after epoch 55900 is 3.1333463\n",
+            "Loss after epoch 55950 is 3.1282442\n",
+            "Loss after epoch 56000 is 3.1231787\n",
+            "Loss after epoch 56050 is 3.1181252\n",
+            "Loss after epoch 56100 is 3.113071\n",
+            "Loss after epoch 56150 is 3.1080308\n",
+            "Loss after epoch 56200 is 3.1029835\n",
+            "Loss after epoch 56250 is 3.0979574\n",
+            "Loss after epoch 56300 is 3.0929272\n",
+            "Loss after epoch 56350 is 3.0879514\n",
+            "Loss after epoch 56400 is 3.082979\n",
+            "Loss after epoch 56450 is 3.078014\n",
+            "Loss after epoch 56500 is 3.0730433\n",
+            "Loss after epoch 56550 is 3.0680923\n",
+            "Loss after epoch 56600 is 3.0631435\n",
+            "Loss after epoch 56650 is 3.058203\n",
+            "Loss after epoch 56700 is 3.0532978\n",
+            "Loss after epoch 56750 is 3.0484061\n",
+            "Loss after epoch 56800 is 3.0435207\n",
+            "Loss after epoch 56850 is 3.0386405\n",
+            "Loss after epoch 56900 is 3.0337672\n",
+            "Loss after epoch 56950 is 3.0288994\n",
+            "Loss after epoch 57000 is 3.0240276\n",
+            "Loss after epoch 57050 is 3.019199\n",
+            "Loss after epoch 57100 is 3.0143878\n",
+            "Loss after epoch 57150 is 3.0095806\n",
+            "Loss after epoch 57200 is 3.0047886\n",
+            "Loss after epoch 57250 is 2.9999945\n",
+            "Loss after epoch 57300 is 2.9952013\n",
+            "Loss after epoch 57350 is 2.9904191\n",
+            "Loss after epoch 57400 is 2.9856572\n",
+            "Loss after epoch 57450 is 2.980924\n",
+            "Loss after epoch 57500 is 2.9762027\n",
+            "Loss after epoch 57550 is 2.9714816\n",
+            "Loss after epoch 57600 is 2.9667728\n",
+            "Loss after epoch 57650 is 2.9620569\n",
+            "Loss after epoch 57700 is 2.9573514\n",
+            "Loss after epoch 57750 is 2.9526656\n",
+            "Loss after epoch 57800 is 2.9480064\n",
+            "Loss after epoch 57850 is 2.9433608\n",
+            "Loss after epoch 57900 is 2.9387262\n",
+            "Loss after epoch 57950 is 2.9340847\n",
+            "Loss after epoch 58000 is 2.929455\n",
+            "Loss after epoch 58050 is 2.924824\n",
+            "Loss after epoch 58100 is 2.9202101\n",
+            "Loss after epoch 58150 is 2.915625\n",
+            "Loss after epoch 58200 is 2.9110556\n",
+            "Loss after epoch 58250 is 2.906492\n",
+            "Loss after epoch 58300 is 2.9019368\n",
+            "Loss after epoch 58350 is 2.8973753\n",
+            "Loss after epoch 58400 is 2.8928275\n",
+            "Loss after epoch 58450 is 2.8882895\n",
+            "Loss after epoch 58500 is 2.8837662\n",
+            "Loss after epoch 58550 is 2.879273\n",
+            "Loss after epoch 58600 is 2.8747847\n",
+            "Loss after epoch 58650 is 2.8703005\n",
+            "Loss after epoch 58700 is 2.8658257\n",
+            "Loss after epoch 58750 is 2.861356\n",
+            "Loss after epoch 58800 is 2.856888\n",
+            "Loss after epoch 58850 is 2.8524256\n",
+            "Loss after epoch 58900 is 2.848007\n",
+            "Loss after epoch 58950 is 2.8435898\n",
+            "Loss after epoch 59000 is 2.839185\n",
+            "Loss after epoch 59050 is 2.8347774\n",
+            "Loss after epoch 59100 is 2.8303902\n",
+            "Loss after epoch 59150 is 2.8259966\n",
+            "Loss after epoch 59200 is 2.8216062\n",
+            "Loss after epoch 59250 is 2.817236\n",
+            "Loss after epoch 59300 is 2.8129041\n",
+            "Loss after epoch 59350 is 2.8085654\n",
+            "Loss after epoch 59400 is 2.8042452\n",
+            "Loss after epoch 59450 is 2.799919\n",
+            "Loss after epoch 59500 is 2.7956061\n",
+            "Loss after epoch 59550 is 2.791291\n",
+            "Loss after epoch 59600 is 2.78699\n",
+            "Loss after epoch 59650 is 2.7827125\n",
+            "Loss after epoch 59700 is 2.7784588\n",
+            "Loss after epoch 59750 is 2.7741969\n",
+            "Loss after epoch 59800 is 2.7699523\n",
+            "Loss after epoch 59850 is 2.7657125\n",
+            "Loss after epoch 59900 is 2.7614665\n",
+            "Loss after epoch 59950 is 2.7572348\n",
+            "Loss after epoch 60000 is 2.753004\n",
+            "Loss after epoch 60050 is 2.748823\n",
+            "Loss after epoch 60100 is 2.7446434\n",
+            "Loss after epoch 60150 is 2.7404687\n",
+            "Loss after epoch 60200 is 2.736298\n",
+            "Loss after epoch 60250 is 2.7321343\n",
+            "Loss after epoch 60300 is 2.7279742\n",
+            "Loss after epoch 60350 is 2.723809\n",
+            "Loss after epoch 60400 is 2.7196672\n",
+            "Loss after epoch 60450 is 2.7155552\n",
+            "Loss after epoch 60500 is 2.7114618\n",
+            "Loss after epoch 60550 is 2.7073615\n",
+            "Loss after epoch 60600 is 2.7032633\n",
+            "Loss after epoch 60650 is 2.699176\n",
+            "Loss after epoch 60700 is 2.6950877\n",
+            "Loss after epoch 60750 is 2.6910062\n",
+            "Loss after epoch 60800 is 2.6869464\n",
+            "Loss after epoch 60850 is 2.6829195\n",
+            "Loss after epoch 60900 is 2.6788838\n",
+            "Loss after epoch 60950 is 2.6748593\n",
+            "Loss after epoch 61000 is 2.6708474\n",
+            "Loss after epoch 61050 is 2.6668298\n",
+            "Loss after epoch 61100 is 2.6628149\n",
+            "Loss after epoch 61150 is 2.658816\n",
+            "Loss after epoch 61200 is 2.654834\n",
+            "Loss after epoch 61250 is 2.650869\n",
+            "Loss after epoch 61300 is 2.6469235\n",
+            "Loss after epoch 61350 is 2.6429727\n",
+            "Loss after epoch 61400 is 2.6390254\n",
+            "Loss after epoch 61450 is 2.6350882\n",
+            "Loss after epoch 61500 is 2.6311476\n",
+            "Loss after epoch 61550 is 2.6272223\n",
+            "Loss after epoch 61600 is 2.6233108\n",
+            "Loss after epoch 61650 is 2.6194272\n",
+            "Loss after epoch 61700 is 2.6155457\n",
+            "Loss after epoch 61750 is 2.6116745\n",
+            "Loss after epoch 61800 is 2.6077986\n",
+            "Loss after epoch 61850 is 2.6039314\n",
+            "Loss after epoch 61900 is 2.6000707\n",
+            "Loss after epoch 61950 is 2.5962105\n",
+            "Loss after epoch 62000 is 2.5923722\n",
+            "Loss after epoch 62050 is 2.5885592\n",
+            "Loss after epoch 62100 is 2.5847507\n",
+            "Loss after epoch 62150 is 2.580959\n",
+            "Loss after epoch 62200 is 2.577157\n",
+            "Loss after epoch 62250 is 2.5733619\n",
+            "Loss after epoch 62300 is 2.5695736\n",
+            "Loss after epoch 62350 is 2.5657856\n",
+            "Loss after epoch 62400 is 2.562007\n",
+            "Loss after epoch 62450 is 2.5582752\n",
+            "Loss after epoch 62500 is 2.5545325\n",
+            "Loss after epoch 62550 is 2.5508018\n",
+            "Loss after epoch 62600 is 2.5470705\n",
+            "Loss after epoch 62650 is 2.543354\n",
+            "Loss after epoch 62700 is 2.5396304\n",
+            "Loss after epoch 62750 is 2.5359159\n",
+            "Loss after epoch 62800 is 2.532205\n",
+            "Loss after epoch 62850 is 2.5285401\n",
+            "Loss after epoch 62900 is 2.52487\n",
+            "Loss after epoch 62950 is 2.5212119\n",
+            "Loss after epoch 63000 is 2.5175505\n",
+            "Loss after epoch 63050 is 2.5139031\n",
+            "Loss after epoch 63100 is 2.5102518\n",
+            "Loss after epoch 63150 is 2.5066123\n",
+            "Loss after epoch 63200 is 2.502967\n",
+            "Loss after epoch 63250 is 2.4993594\n",
+            "Loss after epoch 63300 is 2.495765\n",
+            "Loss after epoch 63350 is 2.4921644\n",
+            "Loss after epoch 63400 is 2.488581\n",
+            "Loss after epoch 63450 is 2.4849992\n",
+            "Loss after epoch 63500 is 2.481414\n",
+            "Loss after epoch 63550 is 2.4778402\n",
+            "Loss after epoch 63600 is 2.474271\n",
+            "Loss after epoch 63650 is 2.4707162\n",
+            "Loss after epoch 63700 is 2.4671907\n",
+            "Loss after epoch 63750 is 2.4636664\n",
+            "Loss after epoch 63800 is 2.4601455\n",
+            "Loss after epoch 63850 is 2.45663\n",
+            "Loss after epoch 63900 is 2.4531214\n",
+            "Loss after epoch 63950 is 2.449615\n",
+            "Loss after epoch 64000 is 2.4461129\n",
+            "Loss after epoch 64050 is 2.4426036\n",
+            "Loss after epoch 64100 is 2.4391499\n",
+            "Loss after epoch 64150 is 2.4356916\n",
+            "Loss after epoch 64200 is 2.432236\n",
+            "Loss after epoch 64250 is 2.4287884\n",
+            "Loss after epoch 64300 is 2.4253445\n",
+            "Loss after epoch 64350 is 2.4219024\n",
+            "Loss after epoch 64400 is 2.418464\n",
+            "Loss after epoch 64450 is 2.4150338\n",
+            "Loss after epoch 64500 is 2.4116173\n",
+            "Loss after epoch 64550 is 2.408234\n",
+            "Loss after epoch 64600 is 2.404843\n",
+            "Loss after epoch 64650 is 2.4014578\n",
+            "Loss after epoch 64700 is 2.398086\n",
+            "Loss after epoch 64750 is 2.3947108\n",
+            "Loss after epoch 64800 is 2.391336\n",
+            "Loss after epoch 64850 is 2.3879757\n",
+            "Loss after epoch 64900 is 2.384609\n",
+            "Loss after epoch 64950 is 2.3812804\n",
+            "Loss after epoch 65000 is 2.3779523\n",
+            "Loss after epoch 65050 is 2.374639\n",
+            "Loss after epoch 65100 is 2.3713264\n",
+            "Loss after epoch 65150 is 2.3680177\n",
+            "Loss after epoch 65200 is 2.3647172\n",
+            "Loss after epoch 65250 is 2.3614104\n",
+            "Loss after epoch 65300 is 2.3581166\n",
+            "Loss after epoch 65350 is 2.3548203\n",
+            "Loss after epoch 65400 is 2.3515682\n",
+            "Loss after epoch 65450 is 2.3483143\n",
+            "Loss after epoch 65500 is 2.3450696\n",
+            "Loss after epoch 65550 is 2.3418176\n",
+            "Loss after epoch 65600 is 2.3385818\n",
+            "Loss after epoch 65650 is 2.3353431\n",
+            "Loss after epoch 65700 is 2.332113\n",
+            "Loss after epoch 65750 is 2.3288848\n",
+            "Loss after epoch 65800 is 2.3256629\n",
+            "Loss after epoch 65850 is 2.3224754\n",
+            "Loss after epoch 65900 is 2.3192887\n",
+            "Loss after epoch 65950 is 2.3161082\n",
+            "Loss after epoch 66000 is 2.3129306\n",
+            "Loss after epoch 66050 is 2.309757\n",
+            "Loss after epoch 66100 is 2.306587\n",
+            "Loss after epoch 66150 is 2.3034194\n",
+            "Loss after epoch 66200 is 2.3002584\n",
+            "Loss after epoch 66250 is 2.2971096\n",
+            "Loss after epoch 66300 is 2.2939887\n",
+            "Loss after epoch 66350 is 2.2908652\n",
+            "Loss after epoch 66400 is 2.287748\n",
+            "Loss after epoch 66450 is 2.2846434\n",
+            "Loss after epoch 66500 is 2.2815318\n",
+            "Loss after epoch 66550 is 2.278428\n",
+            "Loss after epoch 66600 is 2.2753272\n",
+            "Loss after epoch 66650 is 2.272237\n",
+            "Loss after epoch 66700 is 2.2691503\n",
+            "Loss after epoch 66750 is 2.2660944\n",
+            "Loss after epoch 66800 is 2.2630358\n",
+            "Loss after epoch 66850 is 2.2599905\n",
+            "Loss after epoch 66900 is 2.25694\n",
+            "Loss after epoch 66950 is 2.253903\n",
+            "Loss after epoch 67000 is 2.2508607\n",
+            "Loss after epoch 67050 is 2.2478302\n",
+            "Loss after epoch 67100 is 2.2447927\n",
+            "Loss after epoch 67150 is 2.2417727\n",
+            "Loss after epoch 67200 is 2.23878\n",
+            "Loss after epoch 67250 is 2.2357936\n",
+            "Loss after epoch 67300 is 2.2328017\n",
+            "Loss after epoch 67350 is 2.2298224\n",
+            "Loss after epoch 67400 is 2.2268445\n",
+            "Loss after epoch 67450 is 2.2238672\n",
+            "Loss after epoch 67500 is 2.220896\n",
+            "Loss after epoch 67550 is 2.2179234\n",
+            "Loss after epoch 67600 is 2.214965\n",
+            "Loss after epoch 67650 is 2.212035\n",
+            "Loss after epoch 67700 is 2.2091086\n",
+            "Loss after epoch 67750 is 2.2061892\n",
+            "Loss after epoch 67800 is 2.2032707\n",
+            "Loss after epoch 67850 is 2.2003467\n",
+            "Loss after epoch 67900 is 2.1974344\n",
+            "Loss after epoch 67950 is 2.1945286\n",
+            "Loss after epoch 68000 is 2.1916237\n",
+            "Loss after epoch 68050 is 2.1887188\n",
+            "Loss after epoch 68100 is 2.1858466\n",
+            "Loss after epoch 68150 is 2.1829817\n",
+            "Loss after epoch 68200 is 2.180119\n",
+            "Loss after epoch 68250 is 2.17726\n",
+            "Loss after epoch 68300 is 2.1744144\n",
+            "Loss after epoch 68350 is 2.1715634\n",
+            "Loss after epoch 68400 is 2.168713\n",
+            "Loss after epoch 68450 is 2.1658692\n",
+            "Loss after epoch 68500 is 2.1630263\n",
+            "Loss after epoch 68550 is 2.1602046\n",
+            "Loss after epoch 68600 is 2.1573985\n",
+            "Loss after epoch 68650 is 2.1545966\n",
+            "Loss after epoch 68700 is 2.1518064\n",
+            "Loss after epoch 68750 is 2.1490083\n",
+            "Loss after epoch 68800 is 2.1462195\n",
+            "Loss after epoch 68850 is 2.1434386\n",
+            "Loss after epoch 68900 is 2.140651\n",
+            "Loss after epoch 68950 is 2.137869\n",
+            "Loss after epoch 69000 is 2.1350887\n",
+            "Loss after epoch 69050 is 2.132349\n",
+            "Loss after epoch 69100 is 2.1296134\n",
+            "Loss after epoch 69150 is 2.1268725\n",
+            "Loss after epoch 69200 is 2.1241422\n",
+            "Loss after epoch 69250 is 2.1214092\n",
+            "Loss after epoch 69300 is 2.1186845\n",
+            "Loss after epoch 69350 is 2.1159563\n",
+            "Loss after epoch 69400 is 2.1132388\n",
+            "Loss after epoch 69450 is 2.1105173\n",
+            "Loss after epoch 69500 is 2.1078196\n",
+            "Loss after epoch 69550 is 2.1051357\n",
+            "Loss after epoch 69600 is 2.10246\n",
+            "Loss after epoch 69650 is 2.0997863\n",
+            "Loss after epoch 69700 is 2.0971167\n",
+            "Loss after epoch 69750 is 2.094444\n",
+            "Loss after epoch 69800 is 2.0917804\n",
+            "Loss after epoch 69850 is 2.0891216\n",
+            "Loss after epoch 69900 is 2.0864663\n",
+            "Loss after epoch 69950 is 2.083804\n",
+            "Loss after epoch 70000 is 2.081177\n",
+            "Loss after epoch 70050 is 2.0785563\n",
+            "Loss after epoch 70100 is 2.075934\n",
+            "Loss after epoch 70150 is 2.073322\n",
+            "Loss after epoch 70200 is 2.0707111\n",
+            "Loss after epoch 70250 is 2.0681043\n",
+            "Loss after epoch 70300 is 2.0655012\n",
+            "Loss after epoch 70350 is 2.0628996\n",
+            "Loss after epoch 70400 is 2.060303\n",
+            "Loss after epoch 70450 is 2.0577087\n",
+            "Loss after epoch 70500 is 2.055147\n",
+            "Loss after epoch 70550 is 2.0525856\n",
+            "Loss after epoch 70600 is 2.050028\n",
+            "Loss after epoch 70650 is 2.0474746\n",
+            "Loss after epoch 70700 is 2.044922\n",
+            "Loss after epoch 70750 is 2.0423822\n",
+            "Loss after epoch 70800 is 2.039837\n",
+            "Loss after epoch 70850 is 2.037293\n",
+            "Loss after epoch 70900 is 2.0347557\n",
+            "Loss after epoch 70950 is 2.032218\n",
+            "Loss after epoch 71000 is 2.0297143\n",
+            "Loss after epoch 71050 is 2.027215\n",
+            "Loss after epoch 71100 is 2.0247211\n",
+            "Loss after epoch 71150 is 2.022223\n",
+            "Loss after epoch 71200 is 2.0197284\n",
+            "Loss after epoch 71250 is 2.017245\n",
+            "Loss after epoch 71300 is 2.0147595\n",
+            "Loss after epoch 71350 is 2.0122802\n",
+            "Loss after epoch 71400 is 2.0097983\n",
+            "Loss after epoch 71450 is 2.007318\n",
+            "Loss after epoch 71500 is 2.0048747\n",
+            "Loss after epoch 71550 is 2.0024328\n",
+            "Loss after epoch 71600 is 1.9999895\n",
+            "Loss after epoch 71650 is 1.9975584\n",
+            "Loss after epoch 71700 is 1.9951279\n",
+            "Loss after epoch 71750 is 1.9926918\n",
+            "Loss after epoch 71800 is 1.9902669\n",
+            "Loss after epoch 71850 is 1.9878463\n",
+            "Loss after epoch 71900 is 1.9854214\n",
+            "Loss after epoch 71950 is 1.9830041\n",
+            "Loss after epoch 72000 is 1.9806061\n",
+            "Loss after epoch 72050 is 1.9782243\n",
+            "Loss after epoch 72100 is 1.975843\n",
+            "Loss after epoch 72150 is 1.9734578\n",
+            "Loss after epoch 72200 is 1.9710828\n",
+            "Loss after epoch 72250 is 1.9687121\n",
+            "Loss after epoch 72300 is 1.9663407\n",
+            "Loss after epoch 72350 is 1.9639738\n",
+            "Loss after epoch 72400 is 1.961611\n",
+            "Loss after epoch 72450 is 1.9592434\n",
+            "Loss after epoch 72500 is 1.9568987\n",
+            "Loss after epoch 72550 is 1.9545702\n",
+            "Loss after epoch 72600 is 1.952243\n",
+            "Loss after epoch 72650 is 1.94992\n",
+            "Loss after epoch 72700 is 1.9475987\n",
+            "Loss after epoch 72750 is 1.9452801\n",
+            "Loss after epoch 72800 is 1.942965\n",
+            "Loss after epoch 72850 is 1.9406534\n",
+            "Loss after epoch 72900 is 1.9383494\n",
+            "Loss after epoch 72950 is 1.9360439\n",
+            "Loss after epoch 73000 is 1.9337394\n",
+            "Loss after epoch 73050 is 1.9314619\n",
+            "Loss after epoch 73100 is 1.9291922\n",
+            "Loss after epoch 73150 is 1.9269296\n",
+            "Loss after epoch 73200 is 1.9246587\n",
+            "Loss after epoch 73250 is 1.9223968\n",
+            "Loss after epoch 73300 is 1.9201348\n",
+            "Loss after epoch 73350 is 1.9178811\n",
+            "Loss after epoch 73400 is 1.9156237\n",
+            "Loss after epoch 73450 is 1.9133722\n",
+            "Loss after epoch 73500 is 1.9111239\n",
+            "Loss after epoch 73550 is 1.9088854\n",
+            "Loss after epoch 73600 is 1.9066739\n",
+            "Loss after epoch 73650 is 1.9044557\n",
+            "Loss after epoch 73700 is 1.9022472\n",
+            "Loss after epoch 73750 is 1.9000348\n",
+            "Loss after epoch 73800 is 1.897833\n",
+            "Loss after epoch 73850 is 1.8956257\n",
+            "Loss after epoch 73900 is 1.8934276\n",
+            "Loss after epoch 73950 is 1.8912294\n",
+            "Loss after epoch 74000 is 1.889036\n",
+            "Loss after epoch 74050 is 1.8868389\n",
+            "Loss after epoch 74100 is 1.8846686\n",
+            "Loss after epoch 74150 is 1.882512\n",
+            "Loss after epoch 74200 is 1.8803531\n",
+            "Loss after epoch 74250 is 1.8782021\n",
+            "Loss after epoch 74300 is 1.8760439\n",
+            "Loss after epoch 74350 is 1.8738939\n",
+            "Loss after epoch 74400 is 1.8717495\n",
+            "Loss after epoch 74450 is 1.869599\n",
+            "Loss after epoch 74500 is 1.8674583\n",
+            "Loss after epoch 74550 is 1.8653188\n",
+            "Loss after epoch 74600 is 1.8631836\n",
+            "Loss after epoch 74650 is 1.8610739\n",
+            "Loss after epoch 74700 is 1.8589616\n",
+            "Loss after epoch 74750 is 1.8568568\n",
+            "Loss after epoch 74800 is 1.8547581\n",
+            "Loss after epoch 74850 is 1.8526598\n",
+            "Loss after epoch 74900 is 1.8505639\n",
+            "Loss after epoch 74950 is 1.8484702\n",
+            "Loss after epoch 75000 is 1.8463808\n",
+            "Loss after epoch 75050 is 1.8442923\n",
+            "Loss after epoch 75100 is 1.8422045\n",
+            "Loss after epoch 75150 is 1.8401203\n",
+            "Loss after epoch 75200 is 1.8380653\n",
+            "Loss after epoch 75250 is 1.8360114\n",
+            "Loss after epoch 75300 is 1.8339611\n",
+            "Loss after epoch 75350 is 1.8319196\n",
+            "Loss after epoch 75400 is 1.8298717\n",
+            "Loss after epoch 75450 is 1.8278273\n",
+            "Loss after epoch 75500 is 1.8257881\n",
+            "Loss after epoch 75550 is 1.8237491\n",
+            "Loss after epoch 75600 is 1.8217126\n",
+            "Loss after epoch 75650 is 1.819679\n",
+            "Loss after epoch 75700 is 1.8176522\n",
+            "Loss after epoch 75750 is 1.8156447\n",
+            "Loss after epoch 75800 is 1.8136418\n",
+            "Loss after epoch 75850 is 1.8116502\n",
+            "Loss after epoch 75900 is 1.8096524\n",
+            "Loss after epoch 75950 is 1.8076651\n",
+            "Loss after epoch 76000 is 1.8056681\n",
+            "Loss after epoch 76050 is 1.80368\n",
+            "Loss after epoch 76100 is 1.8016976\n",
+            "Loss after epoch 76150 is 1.799713\n",
+            "Loss after epoch 76200 is 1.7977284\n",
+            "Loss after epoch 76250 is 1.7957537\n",
+            "Loss after epoch 76300 is 1.7937938\n",
+            "Loss after epoch 76350 is 1.7918434\n",
+            "Loss after epoch 76400 is 1.7898986\n",
+            "Loss after epoch 76450 is 1.7879566\n",
+            "Loss after epoch 76500 is 1.7860141\n",
+            "Loss after epoch 76550 is 1.7840756\n",
+            "Loss after epoch 76600 is 1.7821368\n",
+            "Loss after epoch 76650 is 1.7802027\n",
+            "Loss after epoch 76700 is 1.7782675\n",
+            "Loss after epoch 76750 is 1.7763419\n",
+            "Loss after epoch 76800 is 1.7744142\n",
+            "Loss after epoch 76850 is 1.7724947\n",
+            "Loss after epoch 76900 is 1.7705978\n",
+            "Loss after epoch 76950 is 1.7687033\n",
+            "Loss after epoch 77000 is 1.7668035\n",
+            "Loss after epoch 77050 is 1.7649162\n",
+            "Loss after epoch 77100 is 1.7630283\n",
+            "Loss after epoch 77150 is 1.7611425\n",
+            "Loss after epoch 77200 is 1.759259\n",
+            "Loss after epoch 77250 is 1.7573794\n",
+            "Loss after epoch 77300 is 1.755493\n",
+            "Loss after epoch 77350 is 1.7536178\n",
+            "Loss after epoch 77400 is 1.751741\n",
+            "Loss after epoch 77450 is 1.7498863\n",
+            "Loss after epoch 77500 is 1.7480398\n",
+            "Loss after epoch 77550 is 1.7461956\n",
+            "Loss after epoch 77600 is 1.7443529\n",
+            "Loss after epoch 77650 is 1.742514\n",
+            "Loss after epoch 77700 is 1.7406764\n",
+            "Loss after epoch 77750 is 1.7388408\n",
+            "Loss after epoch 77800 is 1.737008\n",
+            "Loss after epoch 77850 is 1.7351784\n",
+            "Loss after epoch 77900 is 1.7333541\n",
+            "Loss after epoch 77950 is 1.7315286\n",
+            "Loss after epoch 78000 is 1.7297039\n",
+            "Loss after epoch 78050 is 1.7279046\n",
+            "Loss after epoch 78100 is 1.7261095\n",
+            "Loss after epoch 78150 is 1.7243137\n",
+            "Loss after epoch 78200 is 1.7225286\n",
+            "Loss after epoch 78250 is 1.7207363\n",
+            "Loss after epoch 78300 is 1.7189493\n",
+            "Loss after epoch 78350 is 1.7171624\n",
+            "Loss after epoch 78400 is 1.7153841\n",
+            "Loss after epoch 78450 is 1.7136005\n",
+            "Loss after epoch 78500 is 1.7118235\n",
+            "Loss after epoch 78550 is 1.7100453\n",
+            "Loss after epoch 78600 is 1.7082733\n",
+            "Loss after epoch 78650 is 1.706529\n",
+            "Loss after epoch 78700 is 1.704781\n",
+            "Loss after epoch 78750 is 1.7030394\n",
+            "Loss after epoch 78800 is 1.7012957\n",
+            "Loss after epoch 78850 is 1.6995595\n",
+            "Loss after epoch 78900 is 1.6978202\n",
+            "Loss after epoch 78950 is 1.6960857\n",
+            "Loss after epoch 79000 is 1.6943513\n",
+            "Loss after epoch 79050 is 1.6926222\n",
+            "Loss after epoch 79100 is 1.6908934\n",
+            "Loss after epoch 79150 is 1.6891688\n",
+            "Loss after epoch 79200 is 1.6874417\n",
+            "Loss after epoch 79250 is 1.6857458\n",
+            "Loss after epoch 79300 is 1.6840441\n",
+            "Loss after epoch 79350 is 1.6823516\n",
+            "Loss after epoch 79400 is 1.6806614\n",
+            "Loss after epoch 79450 is 1.6789646\n",
+            "Loss after epoch 79500 is 1.67728\n",
+            "Loss after epoch 79550 is 1.6755923\n",
+            "Loss after epoch 79600 is 1.6739031\n",
+            "Loss after epoch 79650 is 1.6722221\n",
+            "Loss after epoch 79700 is 1.6705436\n",
+            "Loss after epoch 79750 is 1.6688658\n",
+            "Loss after epoch 79800 is 1.6671847\n",
+            "Loss after epoch 79850 is 1.6655332\n",
+            "Loss after epoch 79900 is 1.6638837\n",
+            "Loss after epoch 79950 is 1.6622361\n",
+            "Loss after epoch 80000 is 1.6605887\n",
+            "Loss after epoch 80050 is 1.6589476\n",
+            "Loss after epoch 80100 is 1.6573066\n",
+            "Loss after epoch 80150 is 1.6556681\n",
+            "Loss after epoch 80200 is 1.6540289\n",
+            "Loss after epoch 80250 is 1.6523895\n",
+            "Loss after epoch 80300 is 1.6507549\n",
+            "Loss after epoch 80350 is 1.6491259\n",
+            "Loss after epoch 80400 is 1.6474949\n",
+            "Loss after epoch 80450 is 1.6458836\n",
+            "Loss after epoch 80500 is 1.6442791\n",
+            "Loss after epoch 80550 is 1.6426779\n",
+            "Loss after epoch 80600 is 1.641078\n",
+            "Loss after epoch 80650 is 1.6394804\n",
+            "Loss after epoch 80700 is 1.6378851\n",
+            "Loss after epoch 80750 is 1.6362897\n",
+            "Loss after epoch 80800 is 1.6346973\n",
+            "Loss after epoch 80850 is 1.633115\n",
+            "Loss after epoch 80900 is 1.6315238\n",
+            "Loss after epoch 80950 is 1.6299367\n",
+            "Loss after epoch 81000 is 1.6283522\n",
+            "Loss after epoch 81050 is 1.6267709\n",
+            "Loss after epoch 81100 is 1.6252098\n",
+            "Loss after epoch 81150 is 1.6236591\n",
+            "Loss after epoch 81200 is 1.6221042\n",
+            "Loss after epoch 81250 is 1.6205503\n",
+            "Loss after epoch 81300 is 1.6190022\n",
+            "Loss after epoch 81350 is 1.6174554\n",
+            "Loss after epoch 81400 is 1.6159111\n",
+            "Loss after epoch 81450 is 1.6143641\n",
+            "Loss after epoch 81500 is 1.6128201\n",
+            "Loss after epoch 81550 is 1.6112838\n",
+            "Loss after epoch 81600 is 1.6097404\n",
+            "Loss after epoch 81650 is 1.608203\n",
+            "Loss after epoch 81700 is 1.6066729\n",
+            "Loss after epoch 81750 is 1.6051629\n",
+            "Loss after epoch 81800 is 1.6036572\n",
+            "Loss after epoch 81850 is 1.6021476\n",
+            "Loss after epoch 81900 is 1.6006441\n",
+            "Loss after epoch 81950 is 1.5991365\n",
+            "Loss after epoch 82000 is 1.5976357\n",
+            "Loss after epoch 82050 is 1.5961344\n",
+            "Loss after epoch 82100 is 1.5946379\n",
+            "Loss after epoch 82150 is 1.5931367\n",
+            "Loss after epoch 82200 is 1.5916457\n",
+            "Loss after epoch 82250 is 1.5901536\n",
+            "Loss after epoch 82300 is 1.5886596\n",
+            "Loss after epoch 82350 is 1.5871751\n",
+            "Loss after epoch 82400 is 1.5857129\n",
+            "Loss after epoch 82450 is 1.5842501\n",
+            "Loss after epoch 82500 is 1.5827883\n",
+            "Loss after epoch 82550 is 1.5813298\n",
+            "Loss after epoch 82600 is 1.5798662\n",
+            "Loss after epoch 82650 is 1.5784113\n",
+            "Loss after epoch 82700 is 1.5769558\n",
+            "Loss after epoch 82750 is 1.575505\n",
+            "Loss after epoch 82800 is 1.5740532\n",
+            "Loss after epoch 82850 is 1.5725987\n",
+            "Loss after epoch 82900 is 1.5711535\n",
+            "Loss after epoch 82950 is 1.5697055\n",
+            "Loss after epoch 83000 is 1.5682632\n",
+            "Loss after epoch 83050 is 1.566844\n",
+            "Loss after epoch 83100 is 1.5654199\n",
+            "Loss after epoch 83150 is 1.5640087\n",
+            "Loss after epoch 83200 is 1.5625885\n",
+            "Loss after epoch 83250 is 1.561177\n",
+            "Loss after epoch 83300 is 1.5597632\n",
+            "Loss after epoch 83350 is 1.5583527\n",
+            "Loss after epoch 83400 is 1.5569423\n",
+            "Loss after epoch 83450 is 1.5555359\n",
+            "Loss after epoch 83500 is 1.5541253\n",
+            "Loss after epoch 83550 is 1.5527242\n",
+            "Loss after epoch 83600 is 1.5513211\n",
+            "Loss after epoch 83650 is 1.5499189\n",
+            "Loss after epoch 83700 is 1.5485381\n",
+            "Loss after epoch 83750 is 1.5471616\n",
+            "Loss after epoch 83800 is 1.5457861\n",
+            "Loss after epoch 83850 is 1.5444164\n",
+            "Loss after epoch 83900 is 1.5430456\n",
+            "Loss after epoch 83950 is 1.5416731\n",
+            "Loss after epoch 84000 is 1.5403038\n",
+            "Loss after epoch 84050 is 1.538935\n",
+            "Loss after epoch 84100 is 1.537576\n",
+            "Loss after epoch 84150 is 1.53621\n",
+            "Loss after epoch 84200 is 1.5348512\n",
+            "Loss after epoch 84250 is 1.5334874\n",
+            "Loss after epoch 84300 is 1.5321281\n",
+            "Loss after epoch 84350 is 1.5307767\n",
+            "Loss after epoch 84400 is 1.5294448\n",
+            "Loss after epoch 84450 is 1.52811\n",
+            "Loss after epoch 84500 is 1.5267829\n",
+            "Loss after epoch 84550 is 1.5254518\n",
+            "Loss after epoch 84600 is 1.5241262\n",
+            "Loss after epoch 84650 is 1.5227985\n",
+            "Loss after epoch 84700 is 1.5214779\n",
+            "Loss after epoch 84750 is 1.5201507\n",
+            "Loss after epoch 84800 is 1.5188277\n",
+            "Loss after epoch 84850 is 1.517511\n",
+            "Loss after epoch 84900 is 1.5161927\n",
+            "Loss after epoch 84950 is 1.5148766\n",
+            "Loss after epoch 85000 is 1.5135602\n",
+            "Loss after epoch 85050 is 1.5122573\n",
+            "Loss after epoch 85100 is 1.5109653\n",
+            "Loss after epoch 85150 is 1.5096798\n",
+            "Loss after epoch 85200 is 1.5083878\n",
+            "Loss after epoch 85250 is 1.5071015\n",
+            "Loss after epoch 85300 is 1.5058202\n",
+            "Loss after epoch 85350 is 1.504534\n",
+            "Loss after epoch 85400 is 1.5032521\n",
+            "Loss after epoch 85450 is 1.5019689\n",
+            "Loss after epoch 85500 is 1.5006922\n",
+            "Loss after epoch 85550 is 1.4994146\n",
+            "Loss after epoch 85600 is 1.4981366\n",
+            "Loss after epoch 85650 is 1.4968661\n",
+            "Loss after epoch 85700 is 1.4955924\n",
+            "Loss after epoch 85750 is 1.4943309\n",
+            "Loss after epoch 85800 is 1.4930813\n",
+            "Loss after epoch 85850 is 1.4918357\n",
+            "Loss after epoch 85900 is 1.4905887\n",
+            "Loss after epoch 85950 is 1.489345\n",
+            "Loss after epoch 86000 is 1.4880984\n",
+            "Loss after epoch 86050 is 1.4868562\n",
+            "Loss after epoch 86100 is 1.4856166\n",
+            "Loss after epoch 86150 is 1.4843796\n",
+            "Loss after epoch 86200 is 1.4831403\n",
+            "Loss after epoch 86250 is 1.4819053\n",
+            "Loss after epoch 86300 is 1.4806706\n",
+            "Loss after epoch 86350 is 1.4794391\n",
+            "Loss after epoch 86400 is 1.4782035\n",
+            "Loss after epoch 86450 is 1.4769797\n",
+            "Loss after epoch 86500 is 1.475769\n",
+            "Loss after epoch 86550 is 1.474562\n",
+            "Loss after epoch 86600 is 1.4733562\n",
+            "Loss after epoch 86650 is 1.4721526\n",
+            "Loss after epoch 86700 is 1.4709537\n",
+            "Loss after epoch 86750 is 1.4697517\n",
+            "Loss after epoch 86800 is 1.4685506\n",
+            "Loss after epoch 86850 is 1.4673516\n",
+            "Loss after epoch 86900 is 1.4661527\n",
+            "Loss after epoch 86950 is 1.4649599\n",
+            "Loss after epoch 87000 is 1.4637636\n",
+            "Loss after epoch 87050 is 1.4625723\n",
+            "Loss after epoch 87100 is 1.4613779\n",
+            "Loss after epoch 87150 is 1.4601872\n",
+            "Loss after epoch 87200 is 1.4590157\n",
+            "Loss after epoch 87250 is 1.4578489\n",
+            "Loss after epoch 87300 is 1.4566861\n",
+            "Loss after epoch 87350 is 1.4555193\n",
+            "Loss after epoch 87400 is 1.4543545\n",
+            "Loss after epoch 87450 is 1.4531927\n",
+            "Loss after epoch 87500 is 1.4520341\n",
+            "Loss after epoch 87550 is 1.4508741\n",
+            "Loss after epoch 87600 is 1.449715\n",
+            "Loss after epoch 87650 is 1.448562\n",
+            "Loss after epoch 87700 is 1.447406\n",
+            "Loss after epoch 87750 is 1.4462506\n",
+            "Loss after epoch 87800 is 1.445101\n",
+            "Loss after epoch 87850 is 1.4439478\n",
+            "Loss after epoch 87900 is 1.4427998\n",
+            "Loss after epoch 87950 is 1.4416724\n",
+            "Loss after epoch 88000 is 1.4405433\n",
+            "Loss after epoch 88050 is 1.4394183\n",
+            "Loss after epoch 88100 is 1.4382926\n",
+            "Loss after epoch 88150 is 1.4371706\n",
+            "Loss after epoch 88200 is 1.4360472\n",
+            "Loss after epoch 88250 is 1.4349282\n",
+            "Loss after epoch 88300 is 1.4338139\n",
+            "Loss after epoch 88350 is 1.4327189\n",
+            "Loss after epoch 88400 is 1.4316202\n",
+            "Loss after epoch 88450 is 1.4305257\n",
+            "Loss after epoch 88500 is 1.4294289\n",
+            "Loss after epoch 88550 is 1.4283366\n",
+            "Loss after epoch 88600 is 1.4272445\n",
+            "Loss after epoch 88650 is 1.4261557\n",
+            "Loss after epoch 88700 is 1.4250629\n",
+            "Loss after epoch 88750 is 1.4239768\n",
+            "Loss after epoch 88800 is 1.4228883\n",
+            "Loss after epoch 88850 is 1.421806\n",
+            "Loss after epoch 88900 is 1.4207177\n",
+            "Loss after epoch 88950 is 1.4196353\n",
+            "Loss after epoch 89000 is 1.4185538\n",
+            "Loss after epoch 89050 is 1.4174753\n",
+            "Loss after epoch 89100 is 1.4163935\n",
+            "Loss after epoch 89150 is 1.4153165\n",
+            "Loss after epoch 89200 is 1.4142393\n",
+            "Loss after epoch 89250 is 1.4131657\n",
+            "Loss after epoch 89300 is 1.4120873\n",
+            "Loss after epoch 89350 is 1.4110173\n",
+            "Loss after epoch 89400 is 1.4099447\n",
+            "Loss after epoch 89450 is 1.4088748\n",
+            "Loss after epoch 89500 is 1.4078037\n",
+            "Loss after epoch 89550 is 1.4067361\n",
+            "Loss after epoch 89600 is 1.4056709\n",
+            "Loss after epoch 89650 is 1.4046062\n",
+            "Loss after epoch 89700 is 1.4035386\n",
+            "Loss after epoch 89750 is 1.4024774\n",
+            "Loss after epoch 89800 is 1.4014194\n",
+            "Loss after epoch 89850 is 1.4003949\n",
+            "Loss after epoch 89900 is 1.399375\n",
+            "Loss after epoch 89950 is 1.398352\n",
+            "Loss after epoch 90000 is 1.3973325\n",
+            "Loss after epoch 90050 is 1.3963189\n",
+            "Loss after epoch 90100 is 1.3953013\n",
+            "Loss after epoch 90150 is 1.3942845\n",
+            "Loss after epoch 90200 is 1.3932714\n",
+            "Loss after epoch 90250 is 1.392257\n",
+            "Loss after epoch 90300 is 1.3912483\n",
+            "Loss after epoch 90350 is 1.3902364\n",
+            "Loss after epoch 90400 is 1.3892242\n",
+            "Loss after epoch 90450 is 1.3882174\n",
+            "Loss after epoch 90500 is 1.3872072\n",
+            "Loss after epoch 90550 is 1.3862007\n",
+            "Loss after epoch 90600 is 1.3851992\n",
+            "Loss after epoch 90650 is 1.3841952\n",
+            "Loss after epoch 90700 is 1.3831925\n",
+            "Loss after epoch 90750 is 1.3821905\n",
+            "Loss after epoch 90800 is 1.381189\n",
+            "Loss after epoch 90850 is 1.3801932\n",
+            "Loss after epoch 90900 is 1.3791934\n",
+            "Loss after epoch 90950 is 1.3781959\n",
+            "Loss after epoch 91000 is 1.3772018\n",
+            "Loss after epoch 91050 is 1.3762068\n",
+            "Loss after epoch 91100 is 1.3752171\n",
+            "Loss after epoch 91150 is 1.3742228\n",
+            "Loss after epoch 91200 is 1.3732326\n",
+            "Loss after epoch 91250 is 1.3722425\n",
+            "Loss after epoch 91300 is 1.3712522\n",
+            "Loss after epoch 91350 is 1.370264\n",
+            "Loss after epoch 91400 is 1.3692942\n",
+            "Loss after epoch 91450 is 1.3683496\n",
+            "Loss after epoch 91500 is 1.367399\n",
+            "Loss after epoch 91550 is 1.3664548\n",
+            "Loss after epoch 91600 is 1.365506\n",
+            "Loss after epoch 91650 is 1.3645654\n",
+            "Loss after epoch 91700 is 1.3636225\n",
+            "Loss after epoch 91750 is 1.3626789\n",
+            "Loss after epoch 91800 is 1.3617396\n",
+            "Loss after epoch 91850 is 1.3608018\n",
+            "Loss after epoch 91900 is 1.3598591\n",
+            "Loss after epoch 91950 is 1.358923\n",
+            "Loss after epoch 92000 is 1.3579857\n",
+            "Loss after epoch 92050 is 1.3570511\n",
+            "Loss after epoch 92100 is 1.3561174\n",
+            "Loss after epoch 92150 is 1.355183\n",
+            "Loss after epoch 92200 is 1.3542525\n",
+            "Loss after epoch 92250 is 1.3533223\n",
+            "Loss after epoch 92300 is 1.3523897\n",
+            "Loss after epoch 92350 is 1.3514615\n",
+            "Loss after epoch 92400 is 1.3505312\n",
+            "Loss after epoch 92450 is 1.3496078\n",
+            "Loss after epoch 92500 is 1.3486824\n",
+            "Loss after epoch 92550 is 1.3477561\n",
+            "Loss after epoch 92600 is 1.3468331\n",
+            "Loss after epoch 92650 is 1.3459144\n",
+            "Loss after epoch 92700 is 1.34499\n",
+            "Loss after epoch 92750 is 1.3440706\n",
+            "Loss after epoch 92800 is 1.3431488\n",
+            "Loss after epoch 92850 is 1.3422334\n",
+            "Loss after epoch 92900 is 1.3413179\n",
+            "Loss after epoch 92950 is 1.3403989\n",
+            "Loss after epoch 93000 is 1.3394866\n",
+            "Loss after epoch 93050 is 1.338594\n",
+            "Loss after epoch 93100 is 1.3377182\n",
+            "Loss after epoch 93150 is 1.3368398\n",
+            "Loss after epoch 93200 is 1.3359635\n",
+            "Loss after epoch 93250 is 1.3350884\n",
+            "Loss after epoch 93300 is 1.3342164\n",
+            "Loss after epoch 93350 is 1.3333437\n",
+            "Loss after epoch 93400 is 1.3324711\n",
+            "Loss after epoch 93450 is 1.3316016\n",
+            "Loss after epoch 93500 is 1.3307306\n",
+            "Loss after epoch 93550 is 1.3298624\n",
+            "Loss after epoch 93600 is 1.3289953\n",
+            "Loss after epoch 93650 is 1.3281287\n",
+            "Loss after epoch 93700 is 1.3272653\n",
+            "Loss after epoch 93750 is 1.3264035\n",
+            "Loss after epoch 93800 is 1.325539\n",
+            "Loss after epoch 93850 is 1.3246766\n",
+            "Loss after epoch 93900 is 1.3238149\n",
+            "Loss after epoch 93950 is 1.3229536\n",
+            "Loss after epoch 94000 is 1.3220949\n",
+            "Loss after epoch 94050 is 1.3212352\n",
+            "Loss after epoch 94100 is 1.3203787\n",
+            "Loss after epoch 94150 is 1.3195233\n",
+            "Loss after epoch 94200 is 1.3186681\n",
+            "Loss after epoch 94250 is 1.3178124\n",
+            "Loss after epoch 94300 is 1.3169582\n",
+            "Loss after epoch 94350 is 1.316107\n",
+            "Loss after epoch 94400 is 1.3152559\n",
+            "Loss after epoch 94450 is 1.3144035\n",
+            "Loss after epoch 94500 is 1.3135583\n",
+            "Loss after epoch 94550 is 1.3127098\n",
+            "Loss after epoch 94600 is 1.3118632\n",
+            "Loss after epoch 94650 is 1.311017\n",
+            "Loss after epoch 94700 is 1.3101714\n",
+            "Loss after epoch 94750 is 1.3093383\n",
+            "Loss after epoch 94800 is 1.3085313\n",
+            "Loss after epoch 94850 is 1.3077205\n",
+            "Loss after epoch 94900 is 1.3069155\n",
+            "Loss after epoch 94950 is 1.3061061\n",
+            "Now testing the model in the test set\n",
+            "The final loss is: 1.203853\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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b0o9fWVGw2fQ1uinjUcfFkfFyExKDlmCsUTN/ixaFSo7uaYeGhlKy5IMnFoOD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\nRK5CYII=\n",
+            "text/plain": [
+              "<matplotlib.figure.Figure at 0x7fe57defc1d0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "6GsRZn5dvnmy",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "cell_type": "code",
+      "source": [
+        ""
+      ],
+      "execution_count": 0,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file