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Created using Colaboratory
This commit is contained in:
Thalles Silva
parent
63e46b0d0e
commit
2cc1e5d969
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},
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"cells": [
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{
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@ -51,7 +300,7 @@
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"import matplotlib.pyplot as plt\n",
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"import torchvision"
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],
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"execution_count": null,
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"execution_count": 10,
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"outputs": []
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{
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@ -61,12 +310,12 @@
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputId": "e44ac358-6480-4a5f-a358-6eb6ace26c8b"
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"outputId": "a6477424-66e6-4a59-bef2-42e5cbada7cf"
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},
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"source": [
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"!pip install gdown"
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],
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"execution_count": null,
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"execution_count": 11,
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"outputs": [
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{
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"output_type": "stream",
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@ -77,8 +326,8 @@
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"Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from gdown) (4.41.1)\n",
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"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (1.24.3)\n",
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"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (3.0.4)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (2020.12.5)\n",
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"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (2.10)\n"
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"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (2.10)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->gdown) (2020.12.5)\n"
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],
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"name": "stdout"
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}
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@ -95,7 +344,7 @@
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" 'resnet18_100-epochs_cifar10': '1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C'}\n",
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" return file_id.get(folder_name, \"Model not found.\")"
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],
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"execution_count": null,
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"execution_count": 12,
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"outputs": []
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},
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{
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@ -105,19 +354,19 @@
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputId": "36932a7d-c7e5-492a-f37d-8be6b18f787a"
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"outputId": "da3bc13b-f989-4a19-dc02-5172e5e370c0"
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},
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"source": [
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"folder_name = 'resnet18_100-epochs_stl10'\n",
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"folder_name = 'resnet18_100-epochs_cifar10'\n",
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"file_id = get_file_id_by_model(folder_name)\n",
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"print(folder_name, file_id)"
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],
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"execution_count": null,
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"execution_count": 13,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"resnet18_100-epochs_stl10 14_nH2FkyKbt61cieQDiSbBVNP8-gtwgF\n"
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"resnet18_100-epochs_cifar10 1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C\n"
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],
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"name": "stdout"
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}
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@ -130,7 +379,7 @@
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputId": "8d52756d-707b-4a3f-9e8c-0d191408deab"
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"outputId": "63d1d89d-ad11-48ba-8bb3-4da15b930073"
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},
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"source": [
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"# download and extract model files\n",
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@ -138,45 +387,18 @@
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"os.system('unzip {}'.format(folder_name))\n",
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"!ls"
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],
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"execution_count": null,
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"execution_count": 14,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"checkpoint_0100.pth.tar\n",
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"config.yml\n",
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"events.out.tfevents.1610901470.4cb2c837708d.2683858.0\n",
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"resnet18_100-epochs_stl10.zip\n",
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"sample_data\n",
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"training.log\n"
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],
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"name": "stdout"
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||||
}
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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||||
"id": "ooyhd8piZ1w1",
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||||
"colab": {
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||||
"base_uri": "https://localhost:8080/"
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||||
},
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||||
"outputId": "6ffb73aa-35c5-4df2-bd1f-6de6a235a9e5"
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},
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"source": [
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"!unzip resnet18_100-epochs_stl10"
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],
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"execution_count": null,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Archive: resnet18_100-epochs_stl10.zip\n",
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"replace checkpoint_0100.pth.tar? [y]es, [n]o, [A]ll, [N]one, [r]ename: A\n",
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" inflating: checkpoint_0100.pth.tar \n",
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" inflating: config.yml \n",
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" inflating: events.out.tfevents.1610901470.4cb2c837708d.2683858.0 \n",
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" inflating: training.log \n"
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||||
"events.out.tfevents.1610901418.4cb2c837708d.2683796.0\n",
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"resnet18_100-epochs_cifar10.zip\n",
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"resnet18_100-epochs-cifar10.zip\n",
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"run.log\n",
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"sample_data\n"
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],
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"name": "stdout"
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}
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@ -192,7 +414,7 @@
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"import torchvision.transforms as transforms\n",
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"from torchvision import datasets"
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],
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"execution_count": null,
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"execution_count": 15,
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"outputs": []
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},
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{
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@ -202,13 +424,13 @@
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"colab": {
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||||
"base_uri": "https://localhost:8080/"
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},
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"outputId": "5f58bd9b-4428-4b8c-e271-b47ca6694f34"
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"outputId": "028ac120-c51d-4eb2-cf00-da69aed6e310"
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},
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"source": [
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"device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
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"print(\"Using device:\", device)"
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],
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"execution_count": null,
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"execution_count": 16,
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"outputs": [
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{
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"output_type": "stream",
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@ -253,7 +475,7 @@
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" num_workers=10, drop_last=False, shuffle=shuffle)\n",
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" return train_loader, test_loader"
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],
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"execution_count": null,
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"execution_count": 17,
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"outputs": []
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},
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{
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@ -265,7 +487,7 @@
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"with open(os.path.join('./config.yml')) as file:\n",
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" config = yaml.load(file)"
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],
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"execution_count": null,
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"execution_count": 18,
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"outputs": []
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},
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{
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@ -279,7 +501,7 @@
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"elif config.arch == 'resnet50':\n",
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" model = torchvision.models.resnet50(pretrained=False, num_classes=10).to(device)"
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],
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"execution_count": null,
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||||
"execution_count": 19,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -299,7 +521,7 @@
|
||||
" state_dict[k[len(\"backbone.\"):]] = state_dict[k]\n",
|
||||
" del state_dict[k]"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 20,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -311,7 +533,7 @@
|
||||
"log = model.load_state_dict(state_dict, strict=False)\n",
|
||||
"assert log.missing_keys == ['fc.weight', 'fc.bias']"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 21,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -320,12 +542,19 @@
|
||||
"id": "_GC0a14uWRr6",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/",
|
||||
"height": 102,
|
||||
"height": 117,
|
||||
"referenced_widgets": [
|
||||
"48ebf2f69d1f4f5a9208cd2923eb5eac"
|
||||
"1b97f76ec8314fe3985e9183af3fdd9b",
|
||||
"1d516174fefa4c26a1d9232a9fc7e34b",
|
||||
"f72a8a93cdd14fa4bfdc34fbf1061f1e",
|
||||
"8a684a8419754a86b7b70b9d26b252a4",
|
||||
"1a4df18ac4034be1acc4b8ef56527fd1",
|
||||
"89b38536b9da4cfdb914fd291aca0dfe",
|
||||
"77da6ecf9d63460ab420d41f28bb7f1d",
|
||||
"45b89ec6a3504560b9643422cee95213"
|
||||
]
|
||||
},
|
||||
"outputId": "6c3b86ad-b568-4c68-c1fb-1f7b2abbb6aa"
|
||||
"outputId": "4382995f-e0fa-48fc-d341-71400a06b6d9"
|
||||
},
|
||||
"source": [
|
||||
"if config.dataset_name == 'cifar10':\n",
|
||||
@ -334,12 +563,12 @@
|
||||
" train_loader, test_loader = get_stl10_data_loaders(download=True)\n",
|
||||
"print(\"Dataset:\", config.dataset_name)"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 22,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Downloading http://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz to ./data/stl10_binary.tar.gz\n"
|
||||
"Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./data/cifar-10-python.tar.gz\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
},
|
||||
@ -347,9 +576,9 @@
|
||||
"output_type": "display_data",
|
||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "48ebf2f69d1f4f5a9208cd2923eb5eac",
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
"model_id": "1b97f76ec8314fe3985e9183af3fdd9b",
|
||||
"version_minor": 0,
|
||||
"version_major": 2
|
||||
},
|
||||
"text/plain": [
|
||||
"HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
|
||||
@ -362,9 +591,9 @@
|
||||
{
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Extracting ./data/stl10_binary.tar.gz to ./data\n",
|
||||
"Extracting ./data/cifar-10-python.tar.gz to ./data\n",
|
||||
"Files already downloaded and verified\n",
|
||||
"Dataset: stl10\n"
|
||||
"Dataset: cifar10\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
}
|
||||
@ -384,7 +613,7 @@
|
||||
"parameters = list(filter(lambda p: p.requires_grad, model.parameters()))\n",
|
||||
"assert len(parameters) == 2 # fc.weight, fc.bias"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 23,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -396,7 +625,7 @@
|
||||
"optimizer = torch.optim.Adam(model.parameters(), lr=3e-4, weight_decay=0.0008)\n",
|
||||
"criterion = torch.nn.CrossEntropyLoss().to(device)"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 24,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -421,7 +650,7 @@
|
||||
" res.append(correct_k.mul_(100.0 / batch_size))\n",
|
||||
" return res"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 25,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
@ -431,7 +660,7 @@
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"outputId": "d6127d8e-836f-4e69-a344-fee7e836d63a"
|
||||
"outputId": "48816318-655c-4c2d-b4fa-4549316a8477"
|
||||
},
|
||||
"source": [
|
||||
"epochs = 100\n",
|
||||
@ -467,111 +696,111 @@
|
||||
" top5_accuracy /= (counter + 1)\n",
|
||||
" print(f\"Epoch {epoch}\\tTop1 Train accuracy {top1_train_accuracy.item()}\\tTop1 Test accuracy: {top1_accuracy.item()}\\tTop5 test acc: {top5_accuracy.item()}\")"
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 26,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 0\tTop1 Train accuracy 27.890625\tTop1 Test accuracy: 42.05322265625\tTop5 test acc: 93.29833984375\n",
|
||||
"Epoch 1\tTop1 Train accuracy 49.921875\tTop1 Test accuracy: 54.45556640625\tTop5 test acc: 96.1181640625\n",
|
||||
"Epoch 2\tTop1 Train accuracy 57.3828125\tTop1 Test accuracy: 58.9599609375\tTop5 test acc: 96.9482421875\n",
|
||||
"Epoch 3\tTop1 Train accuracy 60.01953125\tTop1 Test accuracy: 60.38818359375\tTop5 test acc: 97.03369140625\n",
|
||||
"Epoch 4\tTop1 Train accuracy 61.7578125\tTop1 Test accuracy: 61.572265625\tTop5 test acc: 97.1923828125\n",
|
||||
"Epoch 5\tTop1 Train accuracy 62.91015625\tTop1 Test accuracy: 62.21923828125\tTop5 test acc: 97.30224609375\n",
|
||||
"Epoch 6\tTop1 Train accuracy 63.57421875\tTop1 Test accuracy: 62.6220703125\tTop5 test acc: 97.4365234375\n",
|
||||
"Epoch 7\tTop1 Train accuracy 64.12109375\tTop1 Test accuracy: 63.18359375\tTop5 test acc: 97.55859375\n",
|
||||
"Epoch 8\tTop1 Train accuracy 64.82421875\tTop1 Test accuracy: 63.51318359375\tTop5 test acc: 97.57080078125\n",
|
||||
"Epoch 9\tTop1 Train accuracy 65.17578125\tTop1 Test accuracy: 63.80615234375\tTop5 test acc: 97.59521484375\n",
|
||||
"Epoch 10\tTop1 Train accuracy 65.5859375\tTop1 Test accuracy: 64.14794921875\tTop5 test acc: 97.6318359375\n",
|
||||
"Epoch 11\tTop1 Train accuracy 65.80078125\tTop1 Test accuracy: 64.51416015625\tTop5 test acc: 97.61962890625\n",
|
||||
"Epoch 12\tTop1 Train accuracy 66.03515625\tTop1 Test accuracy: 64.70947265625\tTop5 test acc: 97.69287109375\n",
|
||||
"Epoch 13\tTop1 Train accuracy 66.42578125\tTop1 Test accuracy: 64.88037109375\tTop5 test acc: 97.705078125\n",
|
||||
"Epoch 14\tTop1 Train accuracy 66.9140625\tTop1 Test accuracy: 65.07568359375\tTop5 test acc: 97.76611328125\n",
|
||||
"Epoch 15\tTop1 Train accuracy 67.265625\tTop1 Test accuracy: 65.24658203125\tTop5 test acc: 97.81494140625\n",
|
||||
"Epoch 16\tTop1 Train accuracy 67.48046875\tTop1 Test accuracy: 65.46630859375\tTop5 test acc: 97.8515625\n",
|
||||
"Epoch 17\tTop1 Train accuracy 67.6171875\tTop1 Test accuracy: 65.71044921875\tTop5 test acc: 97.86376953125\n",
|
||||
"Epoch 18\tTop1 Train accuracy 67.83203125\tTop1 Test accuracy: 65.966796875\tTop5 test acc: 97.8759765625\n",
|
||||
"Epoch 19\tTop1 Train accuracy 68.0078125\tTop1 Test accuracy: 66.05224609375\tTop5 test acc: 97.88818359375\n",
|
||||
"Epoch 20\tTop1 Train accuracy 68.1640625\tTop1 Test accuracy: 66.17431640625\tTop5 test acc: 97.88818359375\n",
|
||||
"Epoch 21\tTop1 Train accuracy 68.37890625\tTop1 Test accuracy: 66.30859375\tTop5 test acc: 97.900390625\n",
|
||||
"Epoch 22\tTop1 Train accuracy 68.49609375\tTop1 Test accuracy: 66.50390625\tTop5 test acc: 97.88818359375\n",
|
||||
"Epoch 23\tTop1 Train accuracy 68.75\tTop1 Test accuracy: 66.6259765625\tTop5 test acc: 97.91259765625\n",
|
||||
"Epoch 24\tTop1 Train accuracy 68.90625\tTop1 Test accuracy: 66.68701171875\tTop5 test acc: 97.96142578125\n",
|
||||
"Epoch 25\tTop1 Train accuracy 68.984375\tTop1 Test accuracy: 66.8212890625\tTop5 test acc: 97.998046875\n",
|
||||
"Epoch 26\tTop1 Train accuracy 69.39453125\tTop1 Test accuracy: 66.9677734375\tTop5 test acc: 98.0224609375\n",
|
||||
"Epoch 27\tTop1 Train accuracy 69.4921875\tTop1 Test accuracy: 67.1142578125\tTop5 test acc: 98.01025390625\n",
|
||||
"Epoch 28\tTop1 Train accuracy 69.6484375\tTop1 Test accuracy: 67.1630859375\tTop5 test acc: 98.0224609375\n",
|
||||
"Epoch 29\tTop1 Train accuracy 69.7265625\tTop1 Test accuracy: 67.19970703125\tTop5 test acc: 98.03466796875\n",
|
||||
"Epoch 30\tTop1 Train accuracy 69.74609375\tTop1 Test accuracy: 67.24853515625\tTop5 test acc: 98.05908203125\n",
|
||||
"Epoch 31\tTop1 Train accuracy 69.921875\tTop1 Test accuracy: 67.37060546875\tTop5 test acc: 98.03466796875\n",
|
||||
"Epoch 32\tTop1 Train accuracy 70.078125\tTop1 Test accuracy: 67.46826171875\tTop5 test acc: 98.03466796875\n",
|
||||
"Epoch 33\tTop1 Train accuracy 70.25390625\tTop1 Test accuracy: 67.5048828125\tTop5 test acc: 98.0712890625\n",
|
||||
"Epoch 34\tTop1 Train accuracy 70.33203125\tTop1 Test accuracy: 67.59033203125\tTop5 test acc: 98.095703125\n",
|
||||
"Epoch 35\tTop1 Train accuracy 70.48828125\tTop1 Test accuracy: 67.73681640625\tTop5 test acc: 98.13232421875\n",
|
||||
"Epoch 36\tTop1 Train accuracy 70.5859375\tTop1 Test accuracy: 67.83447265625\tTop5 test acc: 98.1201171875\n",
|
||||
"Epoch 37\tTop1 Train accuracy 70.625\tTop1 Test accuracy: 67.85888671875\tTop5 test acc: 98.13232421875\n",
|
||||
"Epoch 38\tTop1 Train accuracy 70.78125\tTop1 Test accuracy: 67.88330078125\tTop5 test acc: 98.13232421875\n",
|
||||
"Epoch 39\tTop1 Train accuracy 70.91796875\tTop1 Test accuracy: 67.919921875\tTop5 test acc: 98.10791015625\n",
|
||||
"Epoch 40\tTop1 Train accuracy 70.95703125\tTop1 Test accuracy: 67.95654296875\tTop5 test acc: 98.10791015625\n",
|
||||
"Epoch 41\tTop1 Train accuracy 71.03515625\tTop1 Test accuracy: 68.00537109375\tTop5 test acc: 98.1201171875\n",
|
||||
"Epoch 42\tTop1 Train accuracy 71.07421875\tTop1 Test accuracy: 68.06640625\tTop5 test acc: 98.15673828125\n",
|
||||
"Epoch 43\tTop1 Train accuracy 71.15234375\tTop1 Test accuracy: 68.12744140625\tTop5 test acc: 98.15673828125\n",
|
||||
"Epoch 44\tTop1 Train accuracy 71.2109375\tTop1 Test accuracy: 68.1396484375\tTop5 test acc: 98.1689453125\n",
|
||||
"Epoch 45\tTop1 Train accuracy 71.25\tTop1 Test accuracy: 68.1396484375\tTop5 test acc: 98.1689453125\n",
|
||||
"Epoch 46\tTop1 Train accuracy 71.46484375\tTop1 Test accuracy: 68.15185546875\tTop5 test acc: 98.193359375\n",
|
||||
"Epoch 47\tTop1 Train accuracy 71.58203125\tTop1 Test accuracy: 68.22509765625\tTop5 test acc: 98.2177734375\n",
|
||||
"Epoch 48\tTop1 Train accuracy 71.6796875\tTop1 Test accuracy: 68.27392578125\tTop5 test acc: 98.22998046875\n",
|
||||
"Epoch 49\tTop1 Train accuracy 71.8359375\tTop1 Test accuracy: 68.3349609375\tTop5 test acc: 98.22998046875\n",
|
||||
"Epoch 50\tTop1 Train accuracy 71.93359375\tTop1 Test accuracy: 68.44482421875\tTop5 test acc: 98.2421875\n",
|
||||
"Epoch 51\tTop1 Train accuracy 72.01171875\tTop1 Test accuracy: 68.4814453125\tTop5 test acc: 98.2177734375\n",
|
||||
"Epoch 52\tTop1 Train accuracy 72.0703125\tTop1 Test accuracy: 68.505859375\tTop5 test acc: 98.2177734375\n",
|
||||
"Epoch 53\tTop1 Train accuracy 72.2265625\tTop1 Test accuracy: 68.54248046875\tTop5 test acc: 98.22998046875\n",
|
||||
"Epoch 54\tTop1 Train accuracy 72.24609375\tTop1 Test accuracy: 68.5791015625\tTop5 test acc: 98.22998046875\n",
|
||||
"Epoch 55\tTop1 Train accuracy 72.34375\tTop1 Test accuracy: 68.65234375\tTop5 test acc: 98.25439453125\n",
|
||||
"Epoch 56\tTop1 Train accuracy 72.421875\tTop1 Test accuracy: 68.71337890625\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 57\tTop1 Train accuracy 72.51953125\tTop1 Test accuracy: 68.71337890625\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 58\tTop1 Train accuracy 72.94921875\tTop1 Test accuracy: 68.76220703125\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 59\tTop1 Train accuracy 72.98828125\tTop1 Test accuracy: 68.83544921875\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 60\tTop1 Train accuracy 73.0859375\tTop1 Test accuracy: 68.88427734375\tTop5 test acc: 98.30322265625\n",
|
||||
"Epoch 61\tTop1 Train accuracy 73.18359375\tTop1 Test accuracy: 68.896484375\tTop5 test acc: 98.32763671875\n",
|
||||
"Epoch 62\tTop1 Train accuracy 73.3984375\tTop1 Test accuracy: 68.88427734375\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 63\tTop1 Train accuracy 73.4375\tTop1 Test accuracy: 68.95751953125\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 64\tTop1 Train accuracy 73.515625\tTop1 Test accuracy: 68.994140625\tTop5 test acc: 98.32763671875\n",
|
||||
"Epoch 65\tTop1 Train accuracy 73.57421875\tTop1 Test accuracy: 68.9697265625\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 66\tTop1 Train accuracy 73.61328125\tTop1 Test accuracy: 69.03076171875\tTop5 test acc: 98.32763671875\n",
|
||||
"Epoch 67\tTop1 Train accuracy 73.671875\tTop1 Test accuracy: 69.07958984375\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 68\tTop1 Train accuracy 73.7109375\tTop1 Test accuracy: 69.12841796875\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 69\tTop1 Train accuracy 73.8671875\tTop1 Test accuracy: 69.20166015625\tTop5 test acc: 98.3154296875\n",
|
||||
"Epoch 70\tTop1 Train accuracy 73.984375\tTop1 Test accuracy: 69.25048828125\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 71\tTop1 Train accuracy 74.00390625\tTop1 Test accuracy: 69.2626953125\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 72\tTop1 Train accuracy 74.00390625\tTop1 Test accuracy: 69.3115234375\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 73\tTop1 Train accuracy 74.0234375\tTop1 Test accuracy: 69.34814453125\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 74\tTop1 Train accuracy 74.140625\tTop1 Test accuracy: 69.37255859375\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 75\tTop1 Train accuracy 74.23828125\tTop1 Test accuracy: 69.4091796875\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 76\tTop1 Train accuracy 74.31640625\tTop1 Test accuracy: 69.4091796875\tTop5 test acc: 98.37646484375\n",
|
||||
"Epoch 77\tTop1 Train accuracy 74.43359375\tTop1 Test accuracy: 69.4091796875\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 78\tTop1 Train accuracy 74.55078125\tTop1 Test accuracy: 69.3603515625\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 79\tTop1 Train accuracy 74.58984375\tTop1 Test accuracy: 69.37255859375\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 80\tTop1 Train accuracy 74.609375\tTop1 Test accuracy: 69.42138671875\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 81\tTop1 Train accuracy 74.6484375\tTop1 Test accuracy: 69.49462890625\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 82\tTop1 Train accuracy 74.6875\tTop1 Test accuracy: 69.47021484375\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 83\tTop1 Train accuracy 74.7265625\tTop1 Test accuracy: 69.5556640625\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 84\tTop1 Train accuracy 74.78515625\tTop1 Test accuracy: 69.59228515625\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 85\tTop1 Train accuracy 74.8828125\tTop1 Test accuracy: 69.6533203125\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 86\tTop1 Train accuracy 74.94140625\tTop1 Test accuracy: 69.677734375\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 87\tTop1 Train accuracy 75.0390625\tTop1 Test accuracy: 69.7509765625\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 88\tTop1 Train accuracy 75.0390625\tTop1 Test accuracy: 69.71435546875\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 89\tTop1 Train accuracy 75.1171875\tTop1 Test accuracy: 69.775390625\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 90\tTop1 Train accuracy 75.21484375\tTop1 Test accuracy: 69.7509765625\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 91\tTop1 Train accuracy 75.25390625\tTop1 Test accuracy: 69.82421875\tTop5 test acc: 98.32763671875\n",
|
||||
"Epoch 92\tTop1 Train accuracy 75.29296875\tTop1 Test accuracy: 69.86083984375\tTop5 test acc: 98.33984375\n",
|
||||
"Epoch 93\tTop1 Train accuracy 75.33203125\tTop1 Test accuracy: 69.88525390625\tTop5 test acc: 98.35205078125\n",
|
||||
"Epoch 94\tTop1 Train accuracy 75.37109375\tTop1 Test accuracy: 69.81201171875\tTop5 test acc: 98.3642578125\n",
|
||||
"Epoch 95\tTop1 Train accuracy 75.37109375\tTop1 Test accuracy: 69.83642578125\tTop5 test acc: 98.37646484375\n",
|
||||
"Epoch 96\tTop1 Train accuracy 75.37109375\tTop1 Test accuracy: 69.83642578125\tTop5 test acc: 98.37646484375\n",
|
||||
"Epoch 97\tTop1 Train accuracy 75.41015625\tTop1 Test accuracy: 69.86083984375\tTop5 test acc: 98.37646484375\n",
|
||||
"Epoch 98\tTop1 Train accuracy 75.41015625\tTop1 Test accuracy: 69.90966796875\tTop5 test acc: 98.37646484375\n",
|
||||
"Epoch 99\tTop1 Train accuracy 75.46875\tTop1 Test accuracy: 69.921875\tTop5 test acc: 98.37646484375\n"
|
||||
"Epoch 0\tTop1 Train accuracy 49.823020935058594\tTop1 Test accuracy: 57.63786697387695\tTop5 test acc: 94.96036529541016\n",
|
||||
"Epoch 1\tTop1 Train accuracy 59.0130729675293\tTop1 Test accuracy: 59.57088851928711\tTop5 test acc: 95.76114654541016\n",
|
||||
"Epoch 2\tTop1 Train accuracy 60.604671478271484\tTop1 Test accuracy: 60.32686233520508\tTop5 test acc: 96.07250213623047\n",
|
||||
"Epoch 3\tTop1 Train accuracy 61.547752380371094\tTop1 Test accuracy: 61.19715118408203\tTop5 test acc: 96.14946746826172\n",
|
||||
"Epoch 4\tTop1 Train accuracy 62.19586944580078\tTop1 Test accuracy: 61.48035430908203\tTop5 test acc: 96.37407684326172\n",
|
||||
"Epoch 5\tTop1 Train accuracy 62.677772521972656\tTop1 Test accuracy: 61.784236907958984\tTop5 test acc: 96.40337371826172\n",
|
||||
"Epoch 6\tTop1 Train accuracy 63.06640625\tTop1 Test accuracy: 62.2346076965332\tTop5 test acc: 96.50102996826172\n",
|
||||
"Epoch 7\tTop1 Train accuracy 63.40122604370117\tTop1 Test accuracy: 62.52527618408203\tTop5 test acc: 96.46196746826172\n",
|
||||
"Epoch 8\tTop1 Train accuracy 63.698577880859375\tTop1 Test accuracy: 62.83777618408203\tTop5 test acc: 96.54009246826172\n",
|
||||
"Epoch 9\tTop1 Train accuracy 63.90983581542969\tTop1 Test accuracy: 63.118682861328125\tTop5 test acc: 96.58892059326172\n",
|
||||
"Epoch 10\tTop1 Train accuracy 64.14102172851562\tTop1 Test accuracy: 63.20772171020508\tTop5 test acc: 96.68657684326172\n",
|
||||
"Epoch 11\tTop1 Train accuracy 64.33633422851562\tTop1 Test accuracy: 63.469093322753906\tTop5 test acc: 96.75609588623047\n",
|
||||
"Epoch 12\tTop1 Train accuracy 64.5057373046875\tTop1 Test accuracy: 63.556983947753906\tTop5 test acc: 96.71703338623047\n",
|
||||
"Epoch 13\tTop1 Train accuracy 64.6436538696289\tTop1 Test accuracy: 63.66325759887695\tTop5 test acc: 96.69750213623047\n",
|
||||
"Epoch 14\tTop1 Train accuracy 64.75326538085938\tTop1 Test accuracy: 63.62419509887695\tTop5 test acc: 96.68773651123047\n",
|
||||
"Epoch 15\tTop1 Train accuracy 64.87284851074219\tTop1 Test accuracy: 63.84650802612305\tTop5 test acc: 96.66820526123047\n",
|
||||
"Epoch 16\tTop1 Train accuracy 64.97688293457031\tTop1 Test accuracy: 64.00276184082031\tTop5 test acc: 96.72563934326172\n",
|
||||
"Epoch 17\tTop1 Train accuracy 65.05500793457031\tTop1 Test accuracy: 63.95392990112305\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 18\tTop1 Train accuracy 65.11439514160156\tTop1 Test accuracy: 64.01252746582031\tTop5 test acc: 96.72563934326172\n",
|
||||
"Epoch 19\tTop1 Train accuracy 65.21205139160156\tTop1 Test accuracy: 64.07112121582031\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 20\tTop1 Train accuracy 65.31169891357422\tTop1 Test accuracy: 64.06135559082031\tTop5 test acc: 96.73540496826172\n",
|
||||
"Epoch 21\tTop1 Train accuracy 65.40338134765625\tTop1 Test accuracy: 64.18830871582031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 22\tTop1 Train accuracy 65.45320129394531\tTop1 Test accuracy: 64.1969223022461\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 23\tTop1 Train accuracy 65.53292083740234\tTop1 Test accuracy: 64.23828125\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 24\tTop1 Train accuracy 65.61064910888672\tTop1 Test accuracy: 64.30549621582031\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 25\tTop1 Train accuracy 65.68638610839844\tTop1 Test accuracy: 64.31526184082031\tTop5 test acc: 96.69634246826172\n",
|
||||
"Epoch 26\tTop1 Train accuracy 65.75055694580078\tTop1 Test accuracy: 64.39338684082031\tTop5 test acc: 96.66704559326172\n",
|
||||
"Epoch 27\tTop1 Train accuracy 65.80635833740234\tTop1 Test accuracy: 64.40315246582031\tTop5 test acc: 96.67681121826172\n",
|
||||
"Epoch 28\tTop1 Train accuracy 65.8581771850586\tTop1 Test accuracy: 64.39338684082031\tTop5 test acc: 96.67681121826172\n",
|
||||
"Epoch 29\tTop1 Train accuracy 65.91397857666016\tTop1 Test accuracy: 64.42268371582031\tTop5 test acc: 96.65727996826172\n",
|
||||
"Epoch 30\tTop1 Train accuracy 65.96340942382812\tTop1 Test accuracy: 64.42268371582031\tTop5 test acc: 96.63774871826172\n",
|
||||
"Epoch 31\tTop1 Train accuracy 66.00127410888672\tTop1 Test accuracy: 64.39338684082031\tTop5 test acc: 96.62798309326172\n",
|
||||
"Epoch 32\tTop1 Train accuracy 66.05707550048828\tTop1 Test accuracy: 64.39338684082031\tTop5 test acc: 96.65727996826172\n",
|
||||
"Epoch 33\tTop1 Train accuracy 66.10092163085938\tTop1 Test accuracy: 64.43244934082031\tTop5 test acc: 96.66704559326172\n",
|
||||
"Epoch 34\tTop1 Train accuracy 66.13480377197266\tTop1 Test accuracy: 64.44221496582031\tTop5 test acc: 96.64751434326172\n",
|
||||
"Epoch 35\tTop1 Train accuracy 66.16669464111328\tTop1 Test accuracy: 64.4801254272461\tTop5 test acc: 96.63774871826172\n",
|
||||
"Epoch 36\tTop1 Train accuracy 66.21452331542969\tTop1 Test accuracy: 64.4801254272461\tTop5 test acc: 96.63774871826172\n",
|
||||
"Epoch 37\tTop1 Train accuracy 66.2547836303711\tTop1 Test accuracy: 64.5191879272461\tTop5 test acc: 96.61821746826172\n",
|
||||
"Epoch 38\tTop1 Train accuracy 66.28069305419922\tTop1 Test accuracy: 64.5582504272461\tTop5 test acc: 96.62798309326172\n",
|
||||
"Epoch 39\tTop1 Train accuracy 66.32653045654297\tTop1 Test accuracy: 64.57662963867188\tTop5 test acc: 96.63774871826172\n",
|
||||
"Epoch 40\tTop1 Train accuracy 66.35881805419922\tTop1 Test accuracy: 64.62431335449219\tTop5 test acc: 96.61821746826172\n",
|
||||
"Epoch 41\tTop1 Train accuracy 66.37077331542969\tTop1 Test accuracy: 64.68290710449219\tTop5 test acc: 96.61821746826172\n",
|
||||
"Epoch 42\tTop1 Train accuracy 66.39269256591797\tTop1 Test accuracy: 64.66337585449219\tTop5 test acc: 96.61821746826172\n",
|
||||
"Epoch 43\tTop1 Train accuracy 66.41262817382812\tTop1 Test accuracy: 64.66337585449219\tTop5 test acc: 96.63774871826172\n",
|
||||
"Epoch 44\tTop1 Train accuracy 66.45248413085938\tTop1 Test accuracy: 64.62431335449219\tTop5 test acc: 96.65727996826172\n",
|
||||
"Epoch 45\tTop1 Train accuracy 66.48238372802734\tTop1 Test accuracy: 64.65361022949219\tTop5 test acc: 96.66704559326172\n",
|
||||
"Epoch 46\tTop1 Train accuracy 66.51825714111328\tTop1 Test accuracy: 64.65361022949219\tTop5 test acc: 96.67681121826172\n",
|
||||
"Epoch 47\tTop1 Train accuracy 66.56608581542969\tTop1 Test accuracy: 64.64384460449219\tTop5 test acc: 96.65727996826172\n",
|
||||
"Epoch 48\tTop1 Train accuracy 66.59996795654297\tTop1 Test accuracy: 64.61454772949219\tTop5 test acc: 96.67681121826172\n",
|
||||
"Epoch 49\tTop1 Train accuracy 66.64381408691406\tTop1 Test accuracy: 64.67314147949219\tTop5 test acc: 96.67681121826172\n",
|
||||
"Epoch 50\tTop1 Train accuracy 66.65178680419922\tTop1 Test accuracy: 64.70243835449219\tTop5 test acc: 96.69519805908203\n",
|
||||
"Epoch 51\tTop1 Train accuracy 66.65178680419922\tTop1 Test accuracy: 64.72196960449219\tTop5 test acc: 96.69519805908203\n",
|
||||
"Epoch 52\tTop1 Train accuracy 66.69363403320312\tTop1 Test accuracy: 64.70358276367188\tTop5 test acc: 96.72449493408203\n",
|
||||
"Epoch 53\tTop1 Train accuracy 66.70957946777344\tTop1 Test accuracy: 64.75241088867188\tTop5 test acc: 96.71472930908203\n",
|
||||
"Epoch 54\tTop1 Train accuracy 66.72552490234375\tTop1 Test accuracy: 64.81100463867188\tTop5 test acc: 96.71472930908203\n",
|
||||
"Epoch 55\tTop1 Train accuracy 66.73548889160156\tTop1 Test accuracy: 64.84892272949219\tTop5 test acc: 96.69519805908203\n",
|
||||
"Epoch 56\tTop1 Train accuracy 66.77734375\tTop1 Test accuracy: 64.82077026367188\tTop5 test acc: 96.71472930908203\n",
|
||||
"Epoch 57\tTop1 Train accuracy 66.78730773925781\tTop1 Test accuracy: 64.81100463867188\tTop5 test acc: 96.73426055908203\n",
|
||||
"Epoch 58\tTop1 Train accuracy 66.8092269897461\tTop1 Test accuracy: 64.82077026367188\tTop5 test acc: 96.73426055908203\n",
|
||||
"Epoch 59\tTop1 Train accuracy 66.82716369628906\tTop1 Test accuracy: 64.81962585449219\tTop5 test acc: 96.74402618408203\n",
|
||||
"Epoch 60\tTop1 Train accuracy 66.84510040283203\tTop1 Test accuracy: 64.83800506591797\tTop5 test acc: 96.74402618408203\n",
|
||||
"Epoch 61\tTop1 Train accuracy 66.875\tTop1 Test accuracy: 64.80009460449219\tTop5 test acc: 96.75379180908203\n",
|
||||
"Epoch 62\tTop1 Train accuracy 66.88894653320312\tTop1 Test accuracy: 64.79032897949219\tTop5 test acc: 96.76355743408203\n",
|
||||
"Epoch 63\tTop1 Train accuracy 66.91127014160156\tTop1 Test accuracy: 64.78056335449219\tTop5 test acc: 96.76355743408203\n",
|
||||
"Epoch 64\tTop1 Train accuracy 66.93319702148438\tTop1 Test accuracy: 64.76103210449219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 65\tTop1 Train accuracy 66.96907043457031\tTop1 Test accuracy: 64.78056335449219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 66\tTop1 Train accuracy 66.97704315185547\tTop1 Test accuracy: 64.79032897949219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 67\tTop1 Train accuracy 67.00494384765625\tTop1 Test accuracy: 64.76103210449219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 68\tTop1 Train accuracy 67.02487182617188\tTop1 Test accuracy: 64.74150085449219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 69\tTop1 Train accuracy 67.04280853271484\tTop1 Test accuracy: 64.73173522949219\tTop5 test acc: 96.78308868408203\n",
|
||||
"Epoch 70\tTop1 Train accuracy 67.04280853271484\tTop1 Test accuracy: 64.77079772949219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 71\tTop1 Train accuracy 67.0447998046875\tTop1 Test accuracy: 64.79032897949219\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 72\tTop1 Train accuracy 67.05078125\tTop1 Test accuracy: 64.75241088867188\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 73\tTop1 Train accuracy 67.06074523925781\tTop1 Test accuracy: 64.76217651367188\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 74\tTop1 Train accuracy 67.07270050048828\tTop1 Test accuracy: 64.74264526367188\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 75\tTop1 Train accuracy 67.0826644897461\tTop1 Test accuracy: 64.7340316772461\tTop5 test acc: 96.77332305908203\n",
|
||||
"Epoch 76\tTop1 Train accuracy 67.09263610839844\tTop1 Test accuracy: 64.7242660522461\tTop5 test acc: 96.78308868408203\n",
|
||||
"Epoch 77\tTop1 Train accuracy 67.1045913696289\tTop1 Test accuracy: 64.6949691772461\tTop5 test acc: 96.76470184326172\n",
|
||||
"Epoch 78\tTop1 Train accuracy 67.1105728149414\tTop1 Test accuracy: 64.6949691772461\tTop5 test acc: 96.75493621826172\n",
|
||||
"Epoch 79\tTop1 Train accuracy 67.13288879394531\tTop1 Test accuracy: 64.6949691772461\tTop5 test acc: 96.75493621826172\n",
|
||||
"Epoch 80\tTop1 Train accuracy 67.13887023925781\tTop1 Test accuracy: 64.7242660522461\tTop5 test acc: 96.76470184326172\n",
|
||||
"Epoch 81\tTop1 Train accuracy 67.14684295654297\tTop1 Test accuracy: 64.7145004272461\tTop5 test acc: 96.76470184326172\n",
|
||||
"Epoch 82\tTop1 Train accuracy 67.17076110839844\tTop1 Test accuracy: 64.7242660522461\tTop5 test acc: 96.75493621826172\n",
|
||||
"Epoch 83\tTop1 Train accuracy 67.20065307617188\tTop1 Test accuracy: 64.71565246582031\tTop5 test acc: 96.75493621826172\n",
|
||||
"Epoch 84\tTop1 Train accuracy 67.21659851074219\tTop1 Test accuracy: 64.72541809082031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 85\tTop1 Train accuracy 67.21061706542969\tTop1 Test accuracy: 64.7437973022461\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 86\tTop1 Train accuracy 67.23851776123047\tTop1 Test accuracy: 64.7535629272461\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 87\tTop1 Train accuracy 67.25247192382812\tTop1 Test accuracy: 64.72541809082031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 88\tTop1 Train accuracy 67.2584457397461\tTop1 Test accuracy: 64.71565246582031\tTop5 test acc: 96.73540496826172\n",
|
||||
"Epoch 89\tTop1 Train accuracy 67.26641845703125\tTop1 Test accuracy: 64.79377746582031\tTop5 test acc: 96.73540496826172\n",
|
||||
"Epoch 90\tTop1 Train accuracy 67.2704086303711\tTop1 Test accuracy: 64.79377746582031\tTop5 test acc: 96.72563934326172\n",
|
||||
"Epoch 91\tTop1 Train accuracy 67.2803726196289\tTop1 Test accuracy: 64.77424621582031\tTop5 test acc: 96.73540496826172\n",
|
||||
"Epoch 92\tTop1 Train accuracy 67.29033660888672\tTop1 Test accuracy: 64.78401184082031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 93\tTop1 Train accuracy 67.29830932617188\tTop1 Test accuracy: 64.78401184082031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 94\tTop1 Train accuracy 67.30429077148438\tTop1 Test accuracy: 64.78401184082031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 95\tTop1 Train accuracy 67.30030059814453\tTop1 Test accuracy: 64.79377746582031\tTop5 test acc: 96.74517059326172\n",
|
||||
"Epoch 96\tTop1 Train accuracy 67.30827331542969\tTop1 Test accuracy: 64.77424621582031\tTop5 test acc: 96.72563934326172\n",
|
||||
"Epoch 97\tTop1 Train accuracy 67.31624603271484\tTop1 Test accuracy: 64.7926254272461\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 98\tTop1 Train accuracy 67.32222747802734\tTop1 Test accuracy: 64.8219223022461\tTop5 test acc: 96.71587371826172\n",
|
||||
"Epoch 99\tTop1 Train accuracy 67.32820129394531\tTop1 Test accuracy: 64.8121566772461\tTop5 test acc: 96.71587371826172\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
}
|
||||
@ -585,7 +814,7 @@
|
||||
"source": [
|
||||
""
|
||||
],
|
||||
"execution_count": null,
|
||||
"execution_count": 26,
|
||||
"outputs": []
|
||||
}
|
||||
]
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user