diff --git a/README.md b/README.md index 471e905..04ab9fd 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ Introduction to Deep Learning using Numpy ----------------------------------------- -+ See `requirements.txt` -+ First, execute `data/download_mnist.sh`, a `BASH` script. -+ Next, open the notebook. ++ See `requirements.txt`. ++ All data should already be available in `data/`. ++ Next, open the notebook using `jupyter notebook`. diff --git a/data/.gitignore b/data/.gitignore index 02c0128..1397432 100644 --- a/data/.gitignore +++ b/data/.gitignore @@ -1,2 +1 @@ *.pkl -*.gz diff --git a/deeplearning.ipynb b/deeplearning.ipynb index 86e76d2..68fde45 100644 --- a/deeplearning.ipynb +++ b/deeplearning.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -28,14 +28,12 @@ "Helper Code\n", "----------------\n", "\n", - "Feel free to skip reading this part, unless you are curious.\n", - "\n", - "NB: You need to run the BASH script in this folder `data/download_mnist.sh` to be able to run the experiments involving MNIST. Do this now." + "Feel free to skip reading this part, unless you are curious." ] }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -212,51 +210,9 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "preprocessed MNIST already exists, skipping preprocessing\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Use helper functions to load the data.\n", "circle_data = get_circles_data()\n", @@ -304,7 +260,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -322,7 +278,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -362,7 +318,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -400,7 +356,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -433,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -446,6 +402,7 @@ " y_one = self.onehot.fit_transform(y.reshape(-1,1))\n", " return y_hat - y_one\n", "\n", + "\n", "def relu_backward(z):\n", " \"\"\"if previous layer pre-activated vals were <= 0, also set z to 0\"\"\"\n", " z[z <= 0] = 0\n", @@ -463,7 +420,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -474,6 +431,7 @@ " W = np.random.uniform(low=-bound, high=bound, size=(n_in, n_out))\n", " return W\n", "\n", + "\n", "def init_b(n_out):\n", " \"\"\"Initializes a bias vector the size of the output layer.\"\"\"\n", " b = np.zeros(n_out)\n", @@ -490,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -582,7 +540,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -652,166 +610,9 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TRAIN [epoch 1]: accuracy=50.8750, loss=0.6877\n", - "VALID [epoch 1]: accuracy=50.2841, loss=0.6800\n", - "TEST [epoch 1]: accuracy=49.9432, loss=0.6865\n", - "TRAIN [epoch 2]: accuracy=51.8750, loss=0.6760\n", - "VALID [epoch 2]: accuracy=53.0682, loss=0.6657\n", - "TEST [epoch 2]: accuracy=51.4773, loss=0.6761\n", - "TRAIN [epoch 3]: accuracy=56.6250, loss=0.6641\n", - "VALID [epoch 3]: accuracy=56.3068, loss=0.6568\n", - "TEST [epoch 3]: accuracy=59.2614, loss=0.6627\n", - "TRAIN [epoch 4]: accuracy=65.2500, loss=0.6498\n", - "VALID [epoch 4]: accuracy=49.1477, loss=0.6526\n", - "TEST [epoch 4]: accuracy=49.3750, loss=0.6544\n", - "TRAIN [epoch 5]: accuracy=64.7500, loss=0.6417\n", - "VALID [epoch 5]: accuracy=59.8864, loss=0.6310\n", - "TEST [epoch 5]: accuracy=59.3182, loss=0.6380\n", - "TRAIN [epoch 6]: accuracy=72.8750, loss=0.6302\n", - "VALID [epoch 6]: accuracy=53.7500, loss=0.6191\n", - "TEST [epoch 6]: accuracy=51.9318, loss=0.6247\n", - "TRAIN [epoch 7]: accuracy=72.8750, loss=0.6172\n", - "VALID [epoch 7]: accuracy=95.0568, loss=0.6059\n", - "TEST [epoch 7]: accuracy=91.5909, loss=0.6122\n", - "TRAIN [epoch 8]: accuracy=86.1250, loss=0.6060\n", - "VALID [epoch 8]: accuracy=95.9659, loss=0.5932\n", - "TEST [epoch 8]: accuracy=90.6818, loss=0.6025\n", - "TRAIN [epoch 9]: accuracy=89.6250, loss=0.5941\n", - "VALID [epoch 9]: accuracy=88.5795, loss=0.5840\n", - "TEST [epoch 9]: accuracy=86.3068, loss=0.5888\n", - "TRAIN [epoch 10]: accuracy=88.6250, loss=0.5831\n", - "VALID [epoch 10]: accuracy=100.0000, loss=0.5700\n", - "TEST [epoch 10]: accuracy=100.0000, loss=0.5775\n", - "TRAIN [epoch 11]: accuracy=96.7500, loss=0.5698\n", - "VALID [epoch 11]: accuracy=100.0000, loss=0.5583\n", - "TEST [epoch 11]: accuracy=100.0000, loss=0.5648\n", - "TRAIN [epoch 12]: accuracy=95.8750, loss=0.5574\n", - "VALID [epoch 12]: accuracy=97.8409, loss=0.5529\n", - "TEST [epoch 12]: accuracy=97.5000, loss=0.5603\n", - "TRAIN [epoch 13]: accuracy=98.5000, loss=0.5471\n", - "VALID [epoch 13]: accuracy=100.0000, loss=0.5327\n", - "TEST [epoch 13]: accuracy=100.0000, loss=0.5423\n", - "TRAIN [epoch 14]: accuracy=99.5000, loss=0.5340\n", - "VALID [epoch 14]: accuracy=100.0000, loss=0.5219\n", - "TEST [epoch 14]: accuracy=100.0000, loss=0.5280\n", - "TRAIN [epoch 15]: accuracy=99.5000, loss=0.5211\n", - "VALID [epoch 15]: accuracy=100.0000, loss=0.5091\n", - "TEST [epoch 15]: accuracy=100.0000, loss=0.5166\n", - "TRAIN [epoch 16]: accuracy=99.8750, loss=0.5097\n", - "VALID [epoch 16]: accuracy=100.0000, loss=0.4932\n", - "TEST [epoch 16]: accuracy=100.0000, loss=0.5034\n", - "TRAIN [epoch 17]: accuracy=100.0000, loss=0.4963\n", - "VALID [epoch 17]: accuracy=100.0000, loss=0.4830\n", - "TEST [epoch 17]: accuracy=100.0000, loss=0.4877\n", - "TRAIN [epoch 18]: accuracy=99.5000, loss=0.4817\n", - "VALID [epoch 18]: accuracy=100.0000, loss=0.4688\n", - "TEST [epoch 18]: accuracy=100.0000, loss=0.4753\n", - "TRAIN [epoch 19]: accuracy=100.0000, loss=0.4689\n", - "VALID [epoch 19]: accuracy=100.0000, loss=0.4563\n", - "TEST [epoch 19]: accuracy=100.0000, loss=0.4649\n", - "TRAIN [epoch 20]: accuracy=100.0000, loss=0.4567\n", - "VALID [epoch 20]: accuracy=100.0000, loss=0.4444\n", - "TEST [epoch 20]: accuracy=100.0000, loss=0.4553\n", - "TRAIN [epoch 21]: accuracy=100.0000, loss=0.4426\n", - "VALID [epoch 21]: accuracy=100.0000, loss=0.4306\n", - "TEST [epoch 21]: accuracy=100.0000, loss=0.4412\n", - "TRAIN [epoch 22]: accuracy=100.0000, loss=0.4298\n", - "VALID [epoch 22]: accuracy=100.0000, loss=0.4171\n", - "TEST [epoch 22]: accuracy=100.0000, loss=0.4241\n", - "TRAIN [epoch 23]: accuracy=100.0000, loss=0.4151\n", - "VALID [epoch 23]: accuracy=100.0000, loss=0.4073\n", - "TEST [epoch 23]: accuracy=100.0000, loss=0.4153\n", - "TRAIN [epoch 24]: accuracy=100.0000, loss=0.4026\n", - "VALID [epoch 24]: accuracy=100.0000, loss=0.3946\n", - "TEST [epoch 24]: accuracy=100.0000, loss=0.4030\n", - "TRAIN [epoch 25]: accuracy=100.0000, loss=0.3890\n", - "VALID [epoch 25]: accuracy=100.0000, loss=0.3786\n", - "TEST [epoch 25]: accuracy=100.0000, loss=0.3903\n", - "TRAIN [epoch 26]: accuracy=100.0000, loss=0.3758\n", - "VALID [epoch 26]: accuracy=100.0000, loss=0.3666\n", - "TEST [epoch 26]: accuracy=100.0000, loss=0.3683\n", - "TRAIN [epoch 27]: accuracy=100.0000, loss=0.3634\n", - "VALID [epoch 27]: accuracy=100.0000, loss=0.3545\n", - "TEST [epoch 27]: accuracy=100.0000, loss=0.3607\n", - "TRAIN [epoch 28]: accuracy=100.0000, loss=0.3492\n", - "VALID [epoch 28]: accuracy=100.0000, loss=0.3424\n", - "TEST [epoch 28]: accuracy=100.0000, loss=0.3442\n", - "TRAIN [epoch 29]: accuracy=100.0000, loss=0.3378\n", - "VALID [epoch 29]: accuracy=100.0000, loss=0.3285\n", - "TEST [epoch 29]: accuracy=100.0000, loss=0.3364\n", - "TRAIN [epoch 30]: accuracy=100.0000, loss=0.3253\n", - "VALID [epoch 30]: accuracy=100.0000, loss=0.3170\n", - "TEST [epoch 30]: accuracy=100.0000, loss=0.3230\n", - "TRAIN [epoch 31]: accuracy=100.0000, loss=0.3126\n", - "VALID [epoch 31]: accuracy=100.0000, loss=0.3050\n", - "TEST [epoch 31]: accuracy=100.0000, loss=0.3081\n", - "TRAIN [epoch 32]: accuracy=100.0000, loss=0.2994\n", - "VALID [epoch 32]: accuracy=100.0000, loss=0.2936\n", - "TEST [epoch 32]: accuracy=100.0000, loss=0.2982\n", - "TRAIN [epoch 33]: accuracy=100.0000, loss=0.2895\n", - "VALID [epoch 33]: accuracy=100.0000, loss=0.2831\n", - "TEST [epoch 33]: accuracy=100.0000, loss=0.2879\n", - "TRAIN [epoch 34]: accuracy=100.0000, loss=0.2779\n", - "VALID [epoch 34]: accuracy=100.0000, loss=0.2698\n", - "TEST [epoch 34]: accuracy=100.0000, loss=0.2752\n", - "TRAIN [epoch 35]: accuracy=100.0000, loss=0.2649\n", - "VALID [epoch 35]: accuracy=100.0000, loss=0.2598\n", - "TEST [epoch 35]: accuracy=100.0000, loss=0.2649\n", - "TRAIN [epoch 36]: accuracy=100.0000, loss=0.2553\n", - "VALID [epoch 36]: accuracy=100.0000, loss=0.2523\n", - "TEST [epoch 36]: accuracy=100.0000, loss=0.2554\n", - "TRAIN [epoch 37]: accuracy=100.0000, loss=0.2454\n", - "VALID [epoch 37]: accuracy=100.0000, loss=0.2400\n", - "TEST [epoch 37]: accuracy=100.0000, loss=0.2427\n", - "TRAIN [epoch 38]: accuracy=100.0000, loss=0.2360\n", - "VALID [epoch 38]: accuracy=100.0000, loss=0.2312\n", - "TEST [epoch 38]: accuracy=100.0000, loss=0.2320\n", - "TRAIN [epoch 39]: accuracy=100.0000, loss=0.2256\n", - "VALID [epoch 39]: accuracy=100.0000, loss=0.2216\n", - "TEST [epoch 39]: accuracy=100.0000, loss=0.2250\n", - "TRAIN [epoch 40]: accuracy=100.0000, loss=0.2166\n", - "VALID [epoch 40]: accuracy=100.0000, loss=0.2119\n", - "TEST [epoch 40]: accuracy=100.0000, loss=0.2151\n", - "TRAIN [epoch 41]: accuracy=100.0000, loss=0.2075\n", - "VALID [epoch 41]: accuracy=100.0000, loss=0.2032\n", - "TEST [epoch 41]: accuracy=100.0000, loss=0.2109\n", - "TRAIN [epoch 42]: accuracy=100.0000, loss=0.1989\n", - "VALID [epoch 42]: accuracy=100.0000, loss=0.1954\n", - "TEST [epoch 42]: accuracy=100.0000, loss=0.1982\n", - "TRAIN [epoch 43]: accuracy=100.0000, loss=0.1909\n", - "VALID [epoch 43]: accuracy=100.0000, loss=0.1891\n", - "TEST [epoch 43]: accuracy=100.0000, loss=0.1912\n", - "TRAIN [epoch 44]: accuracy=100.0000, loss=0.1833\n", - "VALID [epoch 44]: accuracy=100.0000, loss=0.1805\n", - "TEST [epoch 44]: accuracy=100.0000, loss=0.1807\n", - "TRAIN [epoch 45]: accuracy=100.0000, loss=0.1758\n", - "VALID [epoch 45]: accuracy=100.0000, loss=0.1736\n", - "TEST [epoch 45]: accuracy=100.0000, loss=0.1757\n", - "TRAIN [epoch 46]: accuracy=100.0000, loss=0.1692\n", - "VALID [epoch 46]: accuracy=100.0000, loss=0.1664\n", - "TEST [epoch 46]: accuracy=100.0000, loss=0.1687\n", - "TRAIN [epoch 47]: accuracy=100.0000, loss=0.1621\n", - "VALID [epoch 47]: accuracy=100.0000, loss=0.1607\n", - "TEST [epoch 47]: accuracy=100.0000, loss=0.1627\n", - "TRAIN [epoch 48]: accuracy=100.0000, loss=0.1558\n", - "VALID [epoch 48]: accuracy=100.0000, loss=0.1555\n", - "TEST [epoch 48]: accuracy=100.0000, loss=0.1554\n", - "TRAIN [epoch 49]: accuracy=100.0000, loss=0.1493\n", - "VALID [epoch 49]: accuracy=100.0000, loss=0.1498\n", - "TEST [epoch 49]: accuracy=100.0000, loss=0.1489\n", - "TRAIN [epoch 50]: accuracy=100.0000, loss=0.1436\n", - "VALID [epoch 50]: accuracy=100.0000, loss=0.1437\n", - "TEST [epoch 50]: accuracy=100.0000, loss=0.1459\n" - ] - } - ], + "outputs": [], "source": [ "# Circles Data\n", "circles_model = MLP(n_in=2, n_hid=100, n_out=2, lr=0.1)\n", @@ -820,322 +621,9 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TRAIN [epoch 1]: accuracy=81.7918, loss=0.5007\n", - "VALID [epoch 1]: accuracy=82.2584, loss=0.4830\n", - "TEST [epoch 1]: accuracy=81.5895, loss=0.5151\n", - "TRAIN [epoch 2]: accuracy=86.1884, loss=0.3773\n", - "VALID [epoch 2]: accuracy=85.3235, loss=0.3938\n", - "TEST [epoch 2]: accuracy=84.8043, loss=0.4077\n", - "TRAIN [epoch 3]: accuracy=87.5360, loss=0.3404\n", - "VALID [epoch 3]: accuracy=86.8211, loss=0.3634\n", - "TEST [epoch 3]: accuracy=86.0523, loss=0.3890\n", - "TRAIN [epoch 4]: accuracy=88.4917, loss=0.3118\n", - "VALID [epoch 4]: accuracy=85.8027, loss=0.4066\n", - "TEST [epoch 4]: accuracy=85.2336, loss=0.4268\n", - "TRAIN [epoch 5]: accuracy=89.2254, loss=0.2935\n", - "VALID [epoch 5]: accuracy=88.0491, loss=0.3431\n", - "TEST [epoch 5]: accuracy=87.1306, loss=0.3693\n", - "TRAIN [epoch 6]: accuracy=89.7393, loss=0.2782\n", - "VALID [epoch 6]: accuracy=87.0308, loss=0.3703\n", - "TEST [epoch 6]: accuracy=86.4617, loss=0.3942\n", - "TRAIN [epoch 7]: accuracy=90.1611, loss=0.2651\n", - "VALID [epoch 7]: accuracy=86.2121, loss=0.3834\n", - "TEST [epoch 7]: accuracy=85.9125, loss=0.4052\n", - "TRAIN [epoch 8]: accuracy=90.6270, loss=0.2522\n", - "VALID [epoch 8]: accuracy=87.4800, loss=0.3769\n", - "TEST [epoch 8]: accuracy=86.9010, loss=0.4007\n", - "TRAIN [epoch 9]: accuracy=90.9429, loss=0.2419\n", - "VALID [epoch 9]: accuracy=87.7796, loss=0.3540\n", - "TEST [epoch 9]: accuracy=87.1705, loss=0.3742\n", - "TRAIN [epoch 10]: accuracy=91.2928, loss=0.2322\n", - "VALID [epoch 10]: accuracy=87.4700, loss=0.3717\n", - "TEST [epoch 10]: accuracy=86.5116, loss=0.4047\n", - "TRAIN [epoch 11]: accuracy=91.6047, loss=0.2235\n", - "VALID [epoch 11]: accuracy=88.1490, loss=0.3667\n", - "TEST [epoch 11]: accuracy=87.5300, loss=0.4026\n", - "TRAIN [epoch 12]: accuracy=91.9606, loss=0.2162\n", - "VALID [epoch 12]: accuracy=87.6997, loss=0.3761\n", - "TEST [epoch 12]: accuracy=87.1406, loss=0.4175\n", - "TRAIN [epoch 13]: accuracy=92.2565, loss=0.2090\n", - "VALID [epoch 13]: accuracy=85.7328, loss=0.4581\n", - "TEST [epoch 13]: accuracy=84.9541, loss=0.4814\n", - "TRAIN [epoch 14]: accuracy=92.4864, loss=0.2015\n", - "VALID [epoch 14]: accuracy=88.4585, loss=0.3663\n", - "TEST [epoch 14]: accuracy=87.8494, loss=0.4002\n", - "TRAIN [epoch 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accuracy=93.9379, loss=0.1633\n", - "VALID [epoch 21]: accuracy=88.2089, loss=0.4227\n", - "TEST [epoch 21]: accuracy=87.5998, loss=0.4718\n", - "TRAIN [epoch 22]: accuracy=94.0819, loss=0.1589\n", - "VALID [epoch 22]: accuracy=87.3003, loss=0.4385\n", - "TEST [epoch 22]: accuracy=86.8710, loss=0.4780\n", - "TRAIN [epoch 23]: accuracy=94.2318, loss=0.1558\n", - "VALID [epoch 23]: accuracy=86.5315, loss=0.4844\n", - "TEST [epoch 23]: accuracy=85.6330, loss=0.5469\n", - "TRAIN [epoch 24]: accuracy=94.2059, loss=0.1539\n", - "VALID [epoch 24]: accuracy=88.3586, loss=0.4201\n", - "TEST [epoch 24]: accuracy=87.5998, loss=0.4701\n", - "TRAIN [epoch 25]: accuracy=94.4718, loss=0.1471\n", - "VALID [epoch 25]: accuracy=88.2089, loss=0.4280\n", - "TEST [epoch 25]: accuracy=87.2704, loss=0.4689\n", - "TRAIN [epoch 26]: accuracy=94.7497, loss=0.1413\n", - "VALID [epoch 26]: accuracy=88.0192, loss=0.4280\n", - "TEST [epoch 26]: accuracy=87.7596, loss=0.4611\n", - "TRAIN [epoch 27]: accuracy=94.8357, loss=0.1387\n", - "VALID [epoch 27]: accuracy=88.3387, loss=0.4422\n", - "TEST [epoch 27]: accuracy=87.6797, loss=0.4972\n", - "TRAIN [epoch 28]: accuracy=94.8716, loss=0.1371\n", - "VALID [epoch 28]: accuracy=87.6597, loss=0.4694\n", - "TEST [epoch 28]: accuracy=87.0407, loss=0.5117\n", - "TRAIN [epoch 29]: accuracy=94.9576, loss=0.1332\n", - "VALID [epoch 29]: accuracy=88.2089, loss=0.4512\n", - "TEST [epoch 29]: accuracy=87.7496, loss=0.4839\n", - "TRAIN [epoch 30]: accuracy=95.2735, loss=0.1265\n", - "VALID [epoch 30]: accuracy=88.1689, loss=0.4645\n", - "TEST [epoch 30]: accuracy=87.6098, loss=0.5082\n", - "TRAIN [epoch 31]: accuracy=95.2395, loss=0.1266\n", - "VALID [epoch 31]: accuracy=88.2688, loss=0.4486\n", - "TEST [epoch 31]: accuracy=87.7696, loss=0.4989\n", - "TRAIN [epoch 32]: accuracy=95.2375, loss=0.1238\n", - "VALID [epoch 32]: accuracy=87.5000, loss=0.5032\n", - "TEST [epoch 32]: accuracy=87.1506, loss=0.5507\n", - "TRAIN [epoch 33]: accuracy=95.4814, loss=0.1234\n", - "VALID [epoch 33]: accuracy=87.7895, loss=0.4915\n", - "TEST [epoch 33]: accuracy=87.2005, loss=0.5440\n", - "TRAIN [epoch 34]: accuracy=95.5374, loss=0.1189\n", - "VALID [epoch 34]: accuracy=87.9992, loss=0.5061\n", - "TEST [epoch 34]: accuracy=87.3602, loss=0.5499\n", - "TRAIN [epoch 35]: accuracy=95.6494, loss=0.1161\n", - "VALID [epoch 35]: accuracy=88.6082, loss=0.4883\n", - "TEST [epoch 35]: accuracy=87.6797, loss=0.5407\n", - "TRAIN [epoch 36]: accuracy=95.7174, loss=0.1151\n", - "VALID [epoch 36]: accuracy=88.2887, loss=0.4992\n", - "TEST [epoch 36]: accuracy=87.6697, loss=0.5675\n", - "TRAIN [epoch 37]: accuracy=95.8453, loss=0.1105\n", - "VALID [epoch 37]: accuracy=88.3886, loss=0.5008\n", - "TEST [epoch 37]: accuracy=87.9393, loss=0.5494\n", - "TRAIN [epoch 38]: accuracy=95.9613, loss=0.1083\n", - "VALID [epoch 38]: accuracy=88.3886, loss=0.5234\n", - "TEST [epoch 38]: accuracy=87.6398, loss=0.5887\n", - "TRAIN [epoch 39]: accuracy=95.9513, loss=0.1066\n", - "VALID [epoch 39]: accuracy=87.3303, loss=0.5376\n", - "TEST [epoch 39]: accuracy=86.9309, loss=0.5873\n", - "TRAIN [epoch 40]: accuracy=96.1152, loss=0.1031\n", - "VALID [epoch 40]: accuracy=87.5799, loss=0.5380\n", - "TEST [epoch 40]: accuracy=87.3203, loss=0.5922\n", - "TRAIN [epoch 41]: accuracy=96.1552, loss=0.1015\n", - "VALID [epoch 41]: accuracy=87.5699, loss=0.5356\n", - "TEST [epoch 41]: accuracy=87.2005, loss=0.5946\n", - "TRAIN [epoch 42]: accuracy=96.2392, loss=0.1005\n", - "VALID [epoch 42]: accuracy=87.8295, loss=0.5666\n", - "TEST [epoch 42]: accuracy=87.2903, loss=0.6167\n", - "TRAIN [epoch 43]: accuracy=96.3412, loss=0.0974\n", - "VALID [epoch 43]: accuracy=87.8894, loss=0.5510\n", - "TEST [epoch 43]: accuracy=87.7396, loss=0.6056\n", - "TRAIN [epoch 44]: accuracy=96.4131, loss=0.0975\n", - "VALID [epoch 44]: accuracy=88.0591, loss=0.5405\n", - "TEST [epoch 44]: accuracy=87.9193, loss=0.5893\n", - "TRAIN [epoch 45]: accuracy=96.5331, loss=0.0936\n", - "VALID [epoch 45]: accuracy=88.3986, loss=0.5607\n", - "TEST [epoch 45]: accuracy=87.7097, loss=0.6310\n", - "TRAIN [epoch 46]: accuracy=96.5111, loss=0.0924\n", - "VALID [epoch 46]: accuracy=88.1390, loss=0.5603\n", - "TEST [epoch 46]: accuracy=87.4800, loss=0.6196\n", - "TRAIN [epoch 47]: accuracy=96.5631, loss=0.0914\n", - "VALID [epoch 47]: accuracy=87.8395, loss=0.5958\n", - "TEST [epoch 47]: accuracy=87.5000, loss=0.6491\n", - "TRAIN [epoch 48]: accuracy=96.6731, loss=0.0888\n", - "VALID [epoch 48]: accuracy=88.0391, loss=0.5650\n", - "TEST [epoch 48]: accuracy=87.5899, loss=0.6330\n", - "TRAIN [epoch 49]: accuracy=96.7490, loss=0.0868\n", - "VALID [epoch 49]: accuracy=88.3586, loss=0.6059\n", - "TEST [epoch 49]: accuracy=87.6198, loss=0.6802\n", - "TRAIN [epoch 50]: accuracy=96.7330, loss=0.0886\n", - "VALID [epoch 50]: accuracy=88.0891, loss=0.5760\n", - "TEST [epoch 50]: accuracy=87.9293, loss=0.6401\n", - "TRAIN [epoch 51]: accuracy=96.5931, loss=0.0918\n", - "VALID [epoch 51]: accuracy=88.0491, loss=0.6073\n", - "TEST [epoch 51]: accuracy=87.7196, loss=0.6818\n", - "TRAIN [epoch 52]: accuracy=96.6171, loss=0.0929\n", - "VALID [epoch 52]: accuracy=87.8195, loss=0.5999\n", - "TEST [epoch 52]: accuracy=87.4900, loss=0.6802\n", - "TRAIN [epoch 53]: accuracy=96.9690, loss=0.0829\n", - "VALID [epoch 53]: accuracy=88.3886, loss=0.5913\n", - "TEST [epoch 53]: accuracy=88.0891, loss=0.6579\n", - "TRAIN [epoch 54]: accuracy=96.8150, loss=0.0853\n", - "VALID [epoch 54]: accuracy=87.5000, loss=0.6453\n", - "TEST [epoch 54]: accuracy=87.5399, loss=0.7063\n", - "TRAIN [epoch 55]: accuracy=96.9270, loss=0.0804\n", - "VALID [epoch 55]: accuracy=88.4185, loss=0.6210\n", - "TEST [epoch 55]: accuracy=87.7097, loss=0.7174\n", - "TRAIN [epoch 56]: accuracy=97.1349, loss=0.0774\n", - "VALID [epoch 56]: accuracy=88.2388, loss=0.6071\n", - "TEST [epoch 56]: accuracy=88.0591, loss=0.6798\n", - "TRAIN [epoch 57]: accuracy=97.3488, loss=0.0720\n", - "VALID [epoch 57]: accuracy=88.3387, loss=0.6383\n", - "TEST [epoch 57]: accuracy=87.7895, loss=0.7012\n", - "TRAIN [epoch 58]: accuracy=97.2549, loss=0.0732\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VALID [epoch 58]: accuracy=88.3986, loss=0.6249\n", - "TEST [epoch 58]: accuracy=87.5499, loss=0.7219\n", - "TRAIN [epoch 59]: accuracy=97.2889, loss=0.0731\n", - "VALID [epoch 59]: accuracy=88.1290, loss=0.6454\n", - "TEST [epoch 59]: accuracy=87.5499, loss=0.7310\n", - "TRAIN [epoch 60]: accuracy=97.4048, loss=0.0686\n", - "VALID [epoch 60]: accuracy=87.9193, loss=0.6633\n", - "TEST [epoch 60]: accuracy=87.2804, loss=0.7389\n", - "TRAIN [epoch 61]: accuracy=97.3588, loss=0.0691\n", - "VALID [epoch 61]: accuracy=87.9792, loss=0.7030\n", - "TEST [epoch 61]: accuracy=87.2404, loss=0.7901\n", - "TRAIN [epoch 62]: accuracy=97.4128, loss=0.0702\n", - "VALID [epoch 62]: accuracy=88.1090, loss=0.6852\n", - "TEST [epoch 62]: accuracy=87.2204, loss=0.7647\n", - "TRAIN [epoch 63]: accuracy=97.4188, loss=0.0682\n", - "VALID [epoch 63]: accuracy=88.4984, loss=0.6583\n", - "TEST [epoch 63]: accuracy=87.7895, loss=0.7467\n", - "TRAIN [epoch 64]: accuracy=97.4088, loss=0.0707\n", - "VALID [epoch 64]: accuracy=87.3403, loss=0.7529\n", - "TEST [epoch 64]: accuracy=86.4317, loss=0.8580\n", - "TRAIN [epoch 65]: accuracy=97.6088, loss=0.0644\n", - "VALID [epoch 65]: accuracy=87.0407, loss=0.7595\n", - "TEST [epoch 65]: accuracy=86.8011, loss=0.8189\n", - "TRAIN [epoch 66]: accuracy=97.7887, loss=0.0617\n", - "VALID [epoch 66]: accuracy=87.8295, loss=0.7223\n", - "TEST [epoch 66]: accuracy=87.1406, loss=0.7987\n", - "TRAIN [epoch 67]: accuracy=97.6088, loss=0.0635\n", - "VALID [epoch 67]: accuracy=87.7496, loss=0.7349\n", - "TEST [epoch 67]: accuracy=87.3403, loss=0.8381\n", - "TRAIN [epoch 68]: accuracy=97.3089, loss=0.0734\n", - "VALID [epoch 68]: accuracy=88.7280, loss=0.6890\n", - "TEST [epoch 68]: accuracy=87.8894, loss=0.7887\n", - "TRAIN [epoch 69]: accuracy=97.3788, loss=0.0708\n", - "VALID [epoch 69]: accuracy=87.9493, loss=0.7064\n", - "TEST [epoch 69]: accuracy=87.2704, loss=0.8000\n", - "TRAIN [epoch 70]: accuracy=97.5108, loss=0.0669\n", - "VALID [epoch 70]: accuracy=87.8994, loss=0.7319\n", - "TEST [epoch 70]: accuracy=87.3103, loss=0.8323\n", - "TRAIN [epoch 71]: accuracy=97.6907, loss=0.0616\n", - "VALID [epoch 71]: accuracy=87.2404, loss=0.7794\n", - "TEST [epoch 71]: accuracy=86.8111, loss=0.8704\n", - "TRAIN [epoch 72]: accuracy=97.6108, loss=0.0649\n", - "VALID [epoch 72]: accuracy=87.8894, loss=0.7348\n", - "TEST [epoch 72]: accuracy=87.2304, loss=0.8299\n", - "TRAIN [epoch 73]: accuracy=97.7767, loss=0.0598\n", - "VALID [epoch 73]: accuracy=87.7097, loss=0.7936\n", - "TEST [epoch 73]: accuracy=87.1106, loss=0.8992\n", - "TRAIN [epoch 74]: accuracy=97.4368, loss=0.0703\n", - "VALID [epoch 74]: accuracy=87.9393, loss=0.7366\n", - "TEST [epoch 74]: accuracy=87.3103, loss=0.8015\n", - "TRAIN [epoch 75]: accuracy=97.6288, loss=0.0645\n", - "VALID [epoch 75]: accuracy=87.7097, loss=0.7344\n", - "TEST [epoch 75]: accuracy=87.0807, loss=0.8252\n", - "TRAIN [epoch 76]: accuracy=97.6168, loss=0.0659\n", - "VALID [epoch 76]: accuracy=88.1190, loss=0.7839\n", - "TEST [epoch 76]: accuracy=87.6098, loss=0.8715\n", - "TRAIN [epoch 77]: accuracy=97.6767, loss=0.0653\n", - "VALID [epoch 77]: accuracy=87.5499, loss=0.7749\n", - "TEST [epoch 77]: accuracy=87.2105, loss=0.9080\n", - "TRAIN [epoch 78]: accuracy=97.6607, loss=0.0616\n", - "VALID [epoch 78]: accuracy=87.5300, loss=0.7650\n", - "TEST [epoch 78]: accuracy=86.9609, loss=0.8798\n", - "TRAIN [epoch 79]: accuracy=97.8387, loss=0.0578\n", - "VALID [epoch 79]: accuracy=88.1589, loss=0.7252\n", - "TEST [epoch 79]: accuracy=87.7097, loss=0.8445\n", - "TRAIN [epoch 80]: accuracy=98.1526, loss=0.0511\n", - "VALID [epoch 80]: accuracy=87.7596, loss=0.7604\n", - "TEST [epoch 80]: accuracy=87.6697, loss=0.8811\n", - "TRAIN [epoch 81]: accuracy=98.0026, loss=0.0551\n", - "VALID [epoch 81]: accuracy=88.0990, loss=0.8027\n", - "TEST [epoch 81]: accuracy=87.4401, loss=0.9281\n", - "TRAIN [epoch 82]: accuracy=97.9527, loss=0.0566\n", - "VALID [epoch 82]: accuracy=88.2588, loss=0.7659\n", - "TEST [epoch 82]: accuracy=87.4101, loss=0.8811\n", - "TRAIN [epoch 83]: accuracy=98.1546, loss=0.0497\n", - "VALID [epoch 83]: accuracy=88.1789, loss=0.7512\n", - "TEST [epoch 83]: accuracy=87.7596, loss=0.8532\n", - "TRAIN [epoch 84]: accuracy=98.1966, loss=0.0472\n", - "VALID [epoch 84]: accuracy=88.5084, loss=0.7818\n", - "TEST [epoch 84]: accuracy=87.8894, loss=0.9100\n", - "TRAIN [epoch 85]: accuracy=98.2466, loss=0.0467\n", - "VALID [epoch 85]: accuracy=88.1689, loss=0.7564\n", - "TEST [epoch 85]: accuracy=87.6498, loss=0.8989\n", - "TRAIN [epoch 86]: accuracy=98.1466, loss=0.0514\n", - "VALID [epoch 86]: accuracy=88.1989, loss=0.7737\n", - "TEST [epoch 86]: accuracy=87.9293, loss=0.9190\n", - "TRAIN [epoch 87]: accuracy=98.0986, loss=0.0528\n", - "VALID [epoch 87]: accuracy=87.9393, loss=0.8174\n", - "TEST [epoch 87]: accuracy=87.2903, loss=0.9441\n", - "TRAIN [epoch 88]: accuracy=98.1426, loss=0.0511\n", - "VALID [epoch 88]: accuracy=87.5200, loss=0.7641\n", - "TEST [epoch 88]: accuracy=87.3103, loss=0.8797\n", - "TRAIN [epoch 89]: accuracy=98.2086, loss=0.0487\n", - "VALID [epoch 89]: accuracy=88.1989, loss=0.8213\n", - "TEST [epoch 89]: accuracy=87.8095, loss=0.9547\n", - "TRAIN [epoch 90]: accuracy=98.1506, loss=0.0509\n", - "VALID [epoch 90]: accuracy=88.0491, loss=0.8414\n", - "TEST [epoch 90]: accuracy=87.5799, loss=0.9444\n", - "TRAIN [epoch 91]: accuracy=98.1766, loss=0.0500\n", - "VALID [epoch 91]: accuracy=87.9493, loss=0.8735\n", - "TEST [epoch 91]: accuracy=87.1506, loss=0.9945\n", - "TRAIN [epoch 92]: accuracy=98.0386, loss=0.0554\n", - "VALID [epoch 92]: accuracy=87.6498, loss=0.8315\n", - "TEST [epoch 92]: accuracy=87.4800, loss=0.9370\n", - "TRAIN [epoch 93]: accuracy=98.1746, loss=0.0487\n", - "VALID [epoch 93]: accuracy=88.2089, loss=0.8123\n", - "TEST [epoch 93]: accuracy=87.8295, loss=0.9184\n", - "TRAIN [epoch 94]: accuracy=98.2306, loss=0.0476\n", - "VALID [epoch 94]: accuracy=88.0491, loss=0.8924\n", - "TEST [epoch 94]: accuracy=87.2304, loss=0.9903\n", - "TRAIN [epoch 95]: accuracy=98.3625, loss=0.0441\n", - "VALID [epoch 95]: accuracy=88.3486, loss=0.8407\n", - "TEST [epoch 95]: accuracy=87.8594, loss=0.9637\n", - "TRAIN [epoch 96]: accuracy=98.4965, loss=0.0419\n", - "VALID [epoch 96]: accuracy=87.0208, loss=0.8981\n", - "TEST [epoch 96]: accuracy=86.7712, loss=0.9918\n", - "TRAIN [epoch 97]: accuracy=98.3285, loss=0.0461\n", - "VALID [epoch 97]: accuracy=87.8095, loss=0.8465\n", - "TEST [epoch 97]: accuracy=87.4201, loss=0.9507\n", - "TRAIN [epoch 98]: accuracy=98.5345, loss=0.0411\n", - "VALID [epoch 98]: accuracy=87.7995, loss=0.8938\n", - "TEST [epoch 98]: accuracy=87.5599, loss=1.0028\n", - "TRAIN [epoch 99]: accuracy=98.3945, loss=0.0444\n", - "VALID [epoch 99]: accuracy=88.1090, loss=0.8342\n", - "TEST [epoch 99]: accuracy=87.4201, loss=0.9647\n", - "TRAIN [epoch 100]: accuracy=98.4205, loss=0.0439\n", - "VALID [epoch 100]: accuracy=88.2588, loss=0.8837\n", - "TEST [epoch 100]: accuracy=87.7296, loss=1.0130\n" - ] - } - ], + "outputs": [], "source": [ "# MNIST Data\n", "mnist_model = MLP(n_in=784, n_hid=100, n_out=10, lr=0.1)\n", @@ -1152,58 +640,9 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "X_valid = circle_data['X']['valid']\n", "y_valid = circle_data['y']['valid']\n", @@ -1233,50 +672,20 @@ "metadata": {}, "source": [ "Training Curves\n", - "-----------------------" + "-----------------------\n", + "\n", + "+ Note the train, valid, and test losses over epochs for the two . Do you see any evidence of overfitting? Why do you think you do or do not?" ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_results(circles_results, 'circles');\n", "plot_results(mnist_results, 'mnist')" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -1295,7 +704,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.6" + "version": "3.7.4" } }, "nbformat": 4, diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..bed1e93 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,7 @@ +jupyter-client==5.3.3 +jupyter-console==6.0.0 +jupyter-core==4.5.0 +jupyter==1.0.0 +matplotlib==3.1.1 +numpy==1.16.4 +sklearn==0.20.2