DIGITS-CNN/cars/lr-investigations/lr.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "a677dbb1",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib as mpl\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
"id": "49ba8631",
"metadata": {},
"source": [
"# Fixed Learning Rate\n",
"80/10/10 Split, 100/200 epochs\n",
"\n",
"## Index\n",
"0. learning rate\n",
"1. top-1 accuracy\n",
"2. top-5 accuracy\n",
"3. last val loss\n",
"4. last val accuracy"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4d96109f",
"metadata": {},
"outputs": [],
"source": [
"fixed_results_200e = np.array([\n",
" [1e-6, 0.31, 2.84, 5.28, 0.67],\n",
" [1e-5, 0.8, 2.59, 5.28, 0.55],\n",
" [1e-4, 6.98, 17.23, 4.6, 7.41],\n",
" [1e-3, 21.56, 44.72, 4.97, 26.9],\n",
" [5e-3, 39.35, 66.83, 3.34, 43.5],\n",
" [1e-2, 13.65, 30.02, 4.15, 17.46],\n",
" [5e-2, 1.79, 6.73, 5.13, 1.78],\n",
" [1e-1, 0.8, 2.78, 5.29, 0.55]\n",
"])\n",
"\n",
"fixed_results_100e = np.array([\n",
" [1e-6, 0.31, 2.9, 5.28, 0.67],\n",
" [1e-5, 0.8, 2.1, 5.28, 0.55],\n",
" [1e-4, 2.35, 8.28, 5.00, 2.63],\n",
" [1e-3, 18.47, 40.09, 4.55, 23.41],\n",
" [5e-3, 35.52, 63.19, 3.33, 40.93],\n",
" [1e-2, 22.42, 47.19, 3.59, 27.02],\n",
" [5e-2, 2.47, 9.02, 5.07, 2.14],\n",
" [1e-1, 0.8, 2.53, 5.28, 0.55]\n",
"])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "345d4c52",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(fixed_results_200e[:, 0], fixed_results_200e[:, 1], 'x-', label=\"Top-1 Accuracy\")\n",
"plt.plot(fixed_results_200e[:, 0], fixed_results_200e[:, 2], 'x-', label=\"Top-5 Accuracy\")\n",
"plt.plot(fixed_results_200e[:, 0], fixed_results_200e[:, 4], 'x-', label=\"Final Val. Accuracy\")\n",
"\n",
"plt.ylim(0)\n",
"\n",
"plt.title('Model Accuracy for Fixed Learning Rates')\n",
"plt.ylabel('% Accuracy')\n",
"plt.xlabel('Learning Rate')\n",
"\n",
"plt.legend()\n",
"plt.xscale('log')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "4fa68d02",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(fixed_results_200e[:, 0], fixed_results_200e[:, 3], 'x-', label=\"Final Validation Loss\")\n",
"\n",
"# plt.ylim(0)\n",
"\n",
"plt.title('Final Validation Loss for Fixed Learning Rates')\n",
"plt.ylabel('Loss')\n",
"plt.xlabel('Learning Rate')\n",
"\n",
"# plt.legend()\n",
"plt.xscale('log')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "e57035e6",
"metadata": {},
"source": [
"# Step-Down\n",
"80/10/10 Split, 100 epochs\n",
"\n",
"## Index\n",
"0. learning rate\n",
"1. step size\n",
"2. gamma\n",
"3. top-1 accuracy\n",
"4. top-5 accuracy\n",
"5. last val loss\n",
"6. last val accuracy"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b7c2a026",
"metadata": {},
"outputs": [],
"source": [
"step_down_results = np.array([\n",
" [1e-2, 0.33, 0.1, 43.79, 70.85, 2.79, 47.24],\n",
" [1e-2, 0.33, 0.25, 45.52, 73.07, 2.90, 49.88],\n",
" [1e-2, 0.33, 0.5, 45.71, 71.71, 2.89, 49.39],\n",
" [1e-2, 0.33, 0.75, 40.09, 68.19, 3.00, 46.38]\n",
"])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "53e815da",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(step_down_results[:, 2], step_down_results[:, 3], 'x-', label=\"Top-1 Accuracy\")\n",
"plt.plot(step_down_results[:, 2], step_down_results[:, 4], 'x-', label=\"Top-5 Accuracy\")\n",
"plt.plot(step_down_results[:, 2], step_down_results[:, 6], 'x-', label=\"Final Val. Accuracy\")\n",
"\n",
"plt.ylim(0)\n",
"\n",
"plt.title('Model Accuracy for Step Down Learning Rates')\n",
"plt.ylabel('% Accuracy')\n",
"plt.xlabel('Gamma')\n",
"\n",
"plt.legend()\n",
"# plt.xscale('log')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "a37bab2d",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(step_down_results[:, 2], step_down_results[:, 5], 'x-', label=\"Final Validation Loss\")\n",
"\n",
"# plt.ylim(0)\n",
"\n",
"plt.title('Final Validation Loss for Fixed Learning Rates')\n",
"plt.ylabel('Loss')\n",
"plt.xlabel('Gamma')\n",
"\n",
"# plt.legend()\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "080c7fcb",
"metadata": {},
"source": [
"# Exponential Decay\n",
"80/10/10 Split, 100 epochs\n",
"\n",
"## Index\n",
"0. learning rate\n",
"1. decay rate\n",
"2. top-1 accuracy\n",
"3. top-5 accuracy\n",
"4. last val loss\n",
"5. last val accuracy"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ab27ce49",
"metadata": {},
"outputs": [],
"source": [
"exp_results = np.array([\n",
" [1e-2, 0.70, 2.35, 8.09, 4.97, 2.75],\n",
" [1e-2, 0.80, 5.0, 15.57, 4.61, 7.23],\n",
" [1e-2, 0.90, 25.88, 52.5, 3.28, 29.17],\n",
" [1e-2, 0.925, 37.43, 63.37, 3.13, 40.81],\n",
" [1e-2, 0.95, 44.1, 71.22, 2.99, 48.84],\n",
" [1e-2, 0.98, 44.41, 71.83, 3.04, 47.61],\n",
" [1e-2, 0.99, 42.43, 69.55, 3.25, 45.47],\n",
" \n",
" [1e-1, 0.85, 12.91, 34.96, 3.85, 14.89],\n",
" [1e-1, 0.9, 0.8, 2.29, 5.29, 0.55]\n",
"])\n",
"two_results = 7"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "684e1744",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(exp_results[:two_results, 1], exp_results[:two_results, 2], 'x-', label=\"Top-1 Accuracy\")\n",
"plt.plot(exp_results[:two_results, 1], exp_results[:two_results, 3], 'x-', label=\"Top-5 Accuracy\")\n",
"plt.plot(exp_results[:two_results, 1], exp_results[:two_results, 5], 'x-', label=\"Final Val. Accuracy\")\n",
"\n",
"plt.ylim(0)\n",
"\n",
"plt.title('Model Accuracy for Exponential Learning Rates')\n",
"plt.ylabel('% Accuracy')\n",
"plt.xlabel('Decay Rate')\n",
"\n",
"plt.legend()\n",
"# plt.xscale('log')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "87ee3e82",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(exp_results[:two_results, 1], exp_results[:two_results, 4], 'x-', label=\"Final Validation Loss\")\n",
"\n",
"# plt.ylim(0)\n",
"\n",
"plt.title('Final Validation Loss for Fixed Learning Rates')\n",
"plt.ylabel('Loss')\n",
"plt.xlabel('Decay Rate')\n",
"\n",
"# plt.legend()\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "ce1b8019",
"metadata": {},
"source": [
"# Sigmoid Decay\n",
"80/10/10 Split, 100 epochs\n",
"\n",
"## Index\n",
"0. learning rate\n",
"1. step size\n",
"2. gamma\n",
"3. top-1 accuracy\n",
"4. top-5 accuracy\n",
"5. last val loss\n",
"6. last val accuracy"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "c4c39704",
"metadata": {},
"outputs": [],
"source": [
"sig_results = np.array([\n",
" [1e-2, 50, 0.05, 46.94, 72.88, 2.79, 52.94],\n",
" [1e-2, 50, 0.1, 45.95, 73.63, 2.65, 51.29],\n",
" [1e-2, 50, 0.15, 41.94, 68.56, 2.94, 47.49],\n",
" [1e-2, 50, 0.2, 41.82, 68.13, 2.82, 45.16]\n",
"])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "0a2e899f",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(sig_results[:, 2], sig_results[:, 3], 'x-', label=\"Top-1 Accuracy\")\n",
"plt.plot(sig_results[:, 2], sig_results[:, 4], 'x-', label=\"Top-5 Accuracy\")\n",
"plt.plot(sig_results[:, 2], sig_results[:, 6], 'x-', label=\"Final Val. Accuracy\")\n",
"\n",
"plt.ylim(0)\n",
"\n",
"plt.title('Model Accuracy for Sigmoid Learning Rates')\n",
"plt.ylabel('% Accuracy')\n",
"plt.xlabel('Gamma')\n",
"\n",
"plt.legend()\n",
"# plt.xscale('log')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "53b1a3b8",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(sig_results[:, 2], sig_results[:, 5], 'x-', label=\"Final Validation Loss\")\n",
"\n",
"# plt.ylim(0)\n",
"\n",
"plt.title('Final Validation Loss for Fixed Learning Rates')\n",
"plt.ylabel('Loss')\n",
"plt.xlabel('Gamma')\n",
"\n",
"# plt.legend()\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "82bd3a32",
"metadata": {},
"source": [
"# Best\n",
"\n",
"100 Epochs\n",
"\n",
"top-1 accuracy indexes: 1, 3, 2, 3"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "c866fad2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"best_top_1_results = list()\n",
"best_labels = list()\n",
"\n",
"# Fixed\n",
"b_fixed = fixed_results_100e[np.argmax(fixed_results_100e[:, 1])]\n",
"best_top_1_results.append(b_fixed[1:3])\n",
"best_labels.append(f'Fixed\\n{b_fixed[0]}')\n",
"\n",
"# Step Down\n",
"b_sd = step_down_results[np.argmax(step_down_results[:, 3])]\n",
"best_top_1_results.append(b_sd[3:5])\n",
"best_labels.append(f'Step Down\\n{b_sd[0]}, Step: {b_sd[1]}, Gamma: {b_sd[2]}')\n",
"\n",
"# Exp\n",
"b_exp = exp_results[np.argmax(exp_results[:, 2])]\n",
"best_top_1_results.append(b_exp[2:4])\n",
"best_labels.append(f'Exponential Decay\\n{b_exp[0]}, Rate: {b_exp[1]}')\n",
"\n",
"# Sig\n",
"b_sig = sig_results[np.argmax(sig_results[:, 3])]\n",
"best_top_1_results.append(b_sig[3:5])\n",
"best_labels.append(f'Sigmoid Decay\\n{b_sig[0]}, Step: {b_sig[1]}, Gamma: {b_sig[2]}')\n",
"\n",
"# print(best_top_1_results)\n",
"# print(best_labels)\n",
"# print(best_top_1_results)\n",
"plt.barh(range(len(best_labels)), [i[0] for i in best_top_1_results], tick_label=best_labels, label='Top-1')\n",
"plt.barh(range(len(best_labels)), [i[1] - i[0] for i in best_top_1_results], tick_label=best_labels, label='Top-5', left=[i[0] for i in best_top_1_results])\n",
"\n",
"plt.legend()\n",
"plt.grid(axis='x')\n",
"plt.title('Best Test Accuracy for Various Learning Schedule Policies')\n",
"plt.xlabel('% Test Accuracy')\n",
"plt.ylabel('Learning Schedule Policies')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "39bd3540",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}