mirror of https://github.com/sthalles/SimCLR.git
Merge remote-tracking branch 'origin/simclr-refactor' into simclr-refactor
Thalles Silva
commit
9496e6de57
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@ -27,7 +27,7 @@
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"accelerator": "GPU",
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@ -39,15 +39,15 @@
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"IPY_MODEL_a88c31d74f5c40a2b24bcff5a35d216c",
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@ -98,12 +98,12 @@
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"left": null
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"_model_name": "FloatProgressModel",
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@ -118,30 +118,30 @@
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"min": 0,
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"_dom_classes": [],
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"_view_module": "@jupyter-widgets/controls",
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"value": " 170500096/? [00:20<00:00, 54507700.03it/s]",
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"value": " 2640404480/? [00:51<00:00, 32685718.58it/s]",
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"_view_count": null,
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"_view_module_version": "1.5.0",
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"description_tooltip": null,
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"_model_module": "@jupyter-widgets/controls",
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"layout": "IPY_MODEL_a4f82234388e4701a02a9f68a177193a"
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"model_module": "@jupyter-widgets/controls",
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"model_name": "ProgressStyleModel",
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"state": {
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@ -156,7 +156,7 @@
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"_model_module": "@jupyter-widgets/controls"
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"89b38536b9da4cfdb914fd291aca0dfe": {
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"model_module": "@jupyter-widgets/base",
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"model_name": "LayoutModel",
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"state": {
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@ -207,7 +207,7 @@
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"left": null
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}
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},
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"77da6ecf9d63460ab420d41f28bb7f1d": {
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"model_module": "@jupyter-widgets/controls",
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"model_name": "DescriptionStyleModel",
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"state": {
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@ -221,7 +221,7 @@
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"_model_module": "@jupyter-widgets/controls"
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}
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},
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"45b89ec6a3504560b9643422cee95213": {
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"model_module": "@jupyter-widgets/base",
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"model_name": "LayoutModel",
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||||
"state": {
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||||
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@ -310,7 +310,7 @@
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"colab": {
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||||
"base_uri": "https://localhost:8080/"
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||||
},
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||||
"outputId": "a6477424-66e6-4a59-bef2-42e5cbada7cf"
|
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"outputId": "48a2ae15-f672-495b-8d43-9a23b85fa3b8"
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||||
},
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"source": [
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"!pip install gdown"
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@ -324,10 +324,10 @@
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"Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from gdown) (1.15.0)\n",
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"Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from gdown) (2.23.0)\n",
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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: 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: 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: 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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||||
"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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||||
],
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||||
"name": "stdout"
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||||
}
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@ -341,7 +341,8 @@
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"source": [
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"def get_file_id_by_model(folder_name):\n",
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" file_id = {'resnet18_100-epochs_stl10': '14_nH2FkyKbt61cieQDiSbBVNP8-gtwgF',\n",
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" 'resnet18_100-epochs_cifar10': '1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C'}\n",
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" 'resnet18_100-epochs_cifar10': '1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C',\n",
|
||||
" 'resnet50_50-epochs_stl10': '1ByTKAUsdm_X7tLcii6oAEl5qFRqRMZSu'}\n",
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||||
" return file_id.get(folder_name, \"Model not found.\")"
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],
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||||
"execution_count": 12,
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@ -354,10 +355,10 @@
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"colab": {
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||||
"base_uri": "https://localhost:8080/"
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},
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"outputId": "da3bc13b-f989-4a19-dc02-5172e5e370c0"
|
||||
"outputId": "59475430-69d2-45a2-b61b-ae755d5d6e88"
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||||
},
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||||
"source": [
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"folder_name = 'resnet18_100-epochs_cifar10'\n",
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"folder_name = 'resnet50_50-epochs_stl10'\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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@ -366,7 +367,7 @@
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{
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||||
"output_type": "stream",
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||||
"text": [
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||||
"resnet18_100-epochs_cifar10 1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C\n"
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||||
"resnet50_50-epochs_stl10 1ByTKAUsdm_X7tLcii6oAEl5qFRqRMZSu\n"
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],
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"name": "stdout"
|
||||
}
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||||
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@ -379,7 +380,7 @@
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"colab": {
|
||||
"base_uri": "https://localhost:8080/"
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||||
},
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||||
"outputId": "63d1d89d-ad11-48ba-8bb3-4da15b930073"
|
||||
"outputId": "fbaeb858-221b-4d1b-dd90-001a6e713b75"
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||||
},
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||||
"source": [
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"# download and extract model files\n",
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@ -392,13 +393,12 @@
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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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"checkpoint_0040.pth.tar\n",
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"config.yml\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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"events.out.tfevents.1610927742.4cb2c837708d.2694093.0\n",
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"resnet50_50-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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@ -424,7 +424,7 @@
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"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"outputId": "028ac120-c51d-4eb2-cf00-da69aed6e310"
|
||||
"outputId": "7532966e-1c4a-4641-c928-4cda14c53389"
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||||
},
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||||
"source": [
|
||||
"device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
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@ -510,7 +510,7 @@
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"id": "4AIfgq41GuTT"
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||||
},
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"source": [
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||||
"checkpoint = torch.load('checkpoint_0100.pth.tar', map_location=device)\n",
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||||
"checkpoint = torch.load('checkpoint_0040.pth.tar', map_location=device)\n",
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||||
"state_dict = checkpoint['state_dict']\n",
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"\n",
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"for k in list(state_dict.keys()):\n",
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@ -521,7 +521,7 @@
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" state_dict[k[len(\"backbone.\"):]] = state_dict[k]\n",
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" del state_dict[k]"
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],
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"execution_count": 20,
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"execution_count": 21,
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"outputs": []
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||||
},
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{
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@ -533,7 +533,7 @@
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"log = model.load_state_dict(state_dict, strict=False)\n",
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"assert log.missing_keys == ['fc.weight', 'fc.bias']"
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],
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"execution_count": 21,
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"execution_count": 22,
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"outputs": []
|
||||
},
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{
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@ -544,17 +544,17 @@
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"base_uri": "https://localhost:8080/",
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"height": 117,
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||||
"referenced_widgets": [
|
||||
"1b97f76ec8314fe3985e9183af3fdd9b",
|
||||
"1d516174fefa4c26a1d9232a9fc7e34b",
|
||||
"f72a8a93cdd14fa4bfdc34fbf1061f1e",
|
||||
"8a684a8419754a86b7b70b9d26b252a4",
|
||||
"1a4df18ac4034be1acc4b8ef56527fd1",
|
||||
"89b38536b9da4cfdb914fd291aca0dfe",
|
||||
"77da6ecf9d63460ab420d41f28bb7f1d",
|
||||
"45b89ec6a3504560b9643422cee95213"
|
||||
"149b9ce8fb68473a837a77431c12281a",
|
||||
"88cd3db2831e4c13a4a634709700d6b2",
|
||||
"a88c31d74f5c40a2b24bcff5a35d216c",
|
||||
"60c6150177694717a622936b830427b5",
|
||||
"dba019efadee4fdc8c799f309b9a7e70",
|
||||
"5901c2829a554c8ebbd5926610088041",
|
||||
"957362a11d174407979cf17012bf9208",
|
||||
"a4f82234388e4701a02a9f68a177193a"
|
||||
]
|
||||
},
|
||||
"outputId": "4382995f-e0fa-48fc-d341-71400a06b6d9"
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||||
"outputId": "4c2558db-921c-425e-f947-6cc746d8c749"
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},
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"source": [
|
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"if config.dataset_name == 'cifar10':\n",
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@ -563,12 +563,12 @@
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" train_loader, test_loader = get_stl10_data_loaders(download=True)\n",
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"print(\"Dataset:\", config.dataset_name)"
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],
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"execution_count": 22,
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"execution_count": 23,
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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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"Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./data/cifar-10-python.tar.gz\n"
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"Downloading http://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz to ./data/stl10_binary.tar.gz\n"
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],
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"name": "stdout"
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},
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@ -576,7 +576,7 @@
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"output_type": "display_data",
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"data": {
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||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "1b97f76ec8314fe3985e9183af3fdd9b",
|
||||
"model_id": "149b9ce8fb68473a837a77431c12281a",
|
||||
"version_minor": 0,
|
||||
"version_major": 2
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||||
},
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||||
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@ -591,9 +591,9 @@
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{
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||||
"output_type": "stream",
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||||
"text": [
|
||||
"Extracting ./data/cifar-10-python.tar.gz to ./data\n",
|
||||
"Extracting ./data/stl10_binary.tar.gz to ./data\n",
|
||||
"Files already downloaded and verified\n",
|
||||
"Dataset: cifar10\n"
|
||||
"Dataset: stl10\n"
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||||
],
|
||||
"name": "stdout"
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||||
}
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||||
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@ -613,7 +613,7 @@
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"parameters = list(filter(lambda p: p.requires_grad, model.parameters()))\n",
|
||||
"assert len(parameters) == 2 # fc.weight, fc.bias"
|
||||
],
|
||||
"execution_count": 23,
|
||||
"execution_count": 24,
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"outputs": []
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||||
},
|
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{
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||||
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@ -625,7 +625,7 @@
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"optimizer = torch.optim.Adam(model.parameters(), lr=3e-4, weight_decay=0.0008)\n",
|
||||
"criterion = torch.nn.CrossEntropyLoss().to(device)"
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||||
],
|
||||
"execution_count": 24,
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||||
"execution_count": 25,
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"outputs": []
|
||||
},
|
||||
{
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||||
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@ -650,7 +650,7 @@
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|||
" res.append(correct_k.mul_(100.0 / batch_size))\n",
|
||||
" return res"
|
||||
],
|
||||
"execution_count": 25,
|
||||
"execution_count": 26,
|
||||
"outputs": []
|
||||
},
|
||||
{
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|
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@ -660,7 +660,7 @@
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"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"outputId": "48816318-655c-4c2d-b4fa-4549316a8477"
|
||||
"outputId": "5f723b91-5a5e-43eb-ca01-a9b5ae2f1346"
|
||||
},
|
||||
"source": [
|
||||
"epochs = 100\n",
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||||
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@ -696,111 +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": 26,
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||||
"execution_count": 27,
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||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
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||||
"text": [
|
||||
"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"
|
||||
"Epoch 0\tTop1 Train accuracy 28.7109375\tTop1 Test accuracy: 43.75\tTop5 test acc: 93.837890625\n",
|
||||
"Epoch 1\tTop1 Train accuracy 49.37959671020508\tTop1 Test accuracy: 52.8662109375\tTop5 test acc: 95.439453125\n",
|
||||
"Epoch 2\tTop1 Train accuracy 55.257354736328125\tTop1 Test accuracy: 56.45263671875\tTop5 test acc: 95.91796875\n",
|
||||
"Epoch 3\tTop1 Train accuracy 57.51838302612305\tTop1 Test accuracy: 57.39013671875\tTop5 test acc: 96.19384765625\n",
|
||||
"Epoch 4\tTop1 Train accuracy 58.727020263671875\tTop1 Test accuracy: 58.2568359375\tTop5 test acc: 96.435546875\n",
|
||||
"Epoch 5\tTop1 Train accuracy 59.677162170410156\tTop1 Test accuracy: 58.7353515625\tTop5 test acc: 96.50390625\n",
|
||||
"Epoch 6\tTop1 Train accuracy 60.065486907958984\tTop1 Test accuracy: 59.17724609375\tTop5 test acc: 96.708984375\n",
|
||||
"Epoch 7\tTop1 Train accuracy 60.612361907958984\tTop1 Test accuracy: 59.482421875\tTop5 test acc: 96.74560546875\n",
|
||||
"Epoch 8\tTop1 Train accuracy 60.827205657958984\tTop1 Test accuracy: 59.66064453125\tTop5 test acc: 96.77490234375\n",
|
||||
"Epoch 9\tTop1 Train accuracy 61.100643157958984\tTop1 Test accuracy: 60.09521484375\tTop5 test acc: 96.82373046875\n",
|
||||
"Epoch 10\tTop1 Train accuracy 61.52803421020508\tTop1 Test accuracy: 60.3466796875\tTop5 test acc: 96.82861328125\n",
|
||||
"Epoch 11\tTop1 Train accuracy 61.80147171020508\tTop1 Test accuracy: 60.6640625\tTop5 test acc: 96.8896484375\n",
|
||||
"Epoch 12\tTop1 Train accuracy 62.09444046020508\tTop1 Test accuracy: 60.96435546875\tTop5 test acc: 96.99462890625\n",
|
||||
"Epoch 13\tTop1 Train accuracy 62.541358947753906\tTop1 Test accuracy: 61.13037109375\tTop5 test acc: 97.0068359375\n",
|
||||
"Epoch 14\tTop1 Train accuracy 62.853858947753906\tTop1 Test accuracy: 61.34033203125\tTop5 test acc: 97.01904296875\n",
|
||||
"Epoch 15\tTop1 Train accuracy 62.951515197753906\tTop1 Test accuracy: 61.5673828125\tTop5 test acc: 96.99951171875\n",
|
||||
"Epoch 16\tTop1 Train accuracy 63.400733947753906\tTop1 Test accuracy: 61.806640625\tTop5 test acc: 97.0361328125\n",
|
||||
"Epoch 17\tTop1 Train accuracy 63.66958236694336\tTop1 Test accuracy: 61.98974609375\tTop5 test acc: 97.0849609375\n",
|
||||
"Epoch 18\tTop1 Train accuracy 63.82583236694336\tTop1 Test accuracy: 62.265625\tTop5 test acc: 97.07275390625\n",
|
||||
"Epoch 19\tTop1 Train accuracy 64.1187973022461\tTop1 Test accuracy: 62.412109375\tTop5 test acc: 97.09716796875\n",
|
||||
"Epoch 20\tTop1 Train accuracy 64.2750473022461\tTop1 Test accuracy: 62.56591796875\tTop5 test acc: 97.12158203125\n",
|
||||
"Epoch 21\tTop1 Train accuracy 64.4140625\tTop1 Test accuracy: 62.724609375\tTop5 test acc: 97.20703125\n",
|
||||
"Epoch 22\tTop1 Train accuracy 64.53125\tTop1 Test accuracy: 62.90771484375\tTop5 test acc: 97.255859375\n",
|
||||
"Epoch 23\tTop1 Train accuracy 64.6484375\tTop1 Test accuracy: 62.95654296875\tTop5 test acc: 97.29248046875\n",
|
||||
"Epoch 24\tTop1 Train accuracy 64.86328125\tTop1 Test accuracy: 63.12255859375\tTop5 test acc: 97.35595703125\n",
|
||||
"Epoch 25\tTop1 Train accuracy 65.1344223022461\tTop1 Test accuracy: 63.330078125\tTop5 test acc: 97.40478515625\n",
|
||||
"Epoch 26\tTop1 Train accuracy 65.3297348022461\tTop1 Test accuracy: 63.3984375\tTop5 test acc: 97.44873046875\n",
|
||||
"Epoch 27\tTop1 Train accuracy 65.4469223022461\tTop1 Test accuracy: 63.34228515625\tTop5 test acc: 97.412109375\n",
|
||||
"Epoch 28\tTop1 Train accuracy 65.6227035522461\tTop1 Test accuracy: 63.48876953125\tTop5 test acc: 97.412109375\n",
|
||||
"Epoch 29\tTop1 Train accuracy 65.85478210449219\tTop1 Test accuracy: 63.56201171875\tTop5 test acc: 97.42431640625\n",
|
||||
"Epoch 30\tTop1 Train accuracy 66.06732940673828\tTop1 Test accuracy: 63.67431640625\tTop5 test acc: 97.4560546875\n",
|
||||
"Epoch 31\tTop1 Train accuracy 66.20404815673828\tTop1 Test accuracy: 63.80859375\tTop5 test acc: 97.48046875\n",
|
||||
"Epoch 32\tTop1 Train accuracy 66.24080657958984\tTop1 Test accuracy: 63.92578125\tTop5 test acc: 97.5048828125\n",
|
||||
"Epoch 33\tTop1 Train accuracy 66.58777618408203\tTop1 Test accuracy: 63.9990234375\tTop5 test acc: 97.529296875\n",
|
||||
"Epoch 34\tTop1 Train accuracy 66.70496368408203\tTop1 Test accuracy: 64.1455078125\tTop5 test acc: 97.51708984375\n",
|
||||
"Epoch 35\tTop1 Train accuracy 66.80261993408203\tTop1 Test accuracy: 64.20654296875\tTop5 test acc: 97.529296875\n",
|
||||
"Epoch 36\tTop1 Train accuracy 66.91980743408203\tTop1 Test accuracy: 64.32861328125\tTop5 test acc: 97.51708984375\n",
|
||||
"Epoch 37\tTop1 Train accuracy 66.93933868408203\tTop1 Test accuracy: 64.3896484375\tTop5 test acc: 97.51708984375\n",
|
||||
"Epoch 38\tTop1 Train accuracy 66.97840118408203\tTop1 Test accuracy: 64.47021484375\tTop5 test acc: 97.529296875\n",
|
||||
"Epoch 39\tTop1 Train accuracy 67.11282348632812\tTop1 Test accuracy: 64.53125\tTop5 test acc: 97.56591796875\n",
|
||||
"Epoch 40\tTop1 Train accuracy 67.24954223632812\tTop1 Test accuracy: 64.6044921875\tTop5 test acc: 97.6025390625\n",
|
||||
"Epoch 41\tTop1 Train accuracy 67.34949493408203\tTop1 Test accuracy: 64.62890625\tTop5 test acc: 97.59033203125\n",
|
||||
"Epoch 42\tTop1 Train accuracy 67.42761993408203\tTop1 Test accuracy: 64.7265625\tTop5 test acc: 97.6025390625\n",
|
||||
"Epoch 43\tTop1 Train accuracy 67.52527618408203\tTop1 Test accuracy: 64.84375\tTop5 test acc: 97.61474609375\n",
|
||||
"Epoch 44\tTop1 Train accuracy 67.58386993408203\tTop1 Test accuracy: 64.87548828125\tTop5 test acc: 97.61474609375\n",
|
||||
"Epoch 45\tTop1 Train accuracy 67.64246368408203\tTop1 Test accuracy: 64.9365234375\tTop5 test acc: 97.626953125\n",
|
||||
"Epoch 46\tTop1 Train accuracy 67.75735473632812\tTop1 Test accuracy: 65.0341796875\tTop5 test acc: 97.66357421875\n",
|
||||
"Epoch 47\tTop1 Train accuracy 67.85501098632812\tTop1 Test accuracy: 65.1318359375\tTop5 test acc: 97.7001953125\n",
|
||||
"Epoch 48\tTop1 Train accuracy 67.89407348632812\tTop1 Test accuracy: 65.1318359375\tTop5 test acc: 97.73681640625\n",
|
||||
"Epoch 49\tTop1 Train accuracy 67.95266723632812\tTop1 Test accuracy: 65.15625\tTop5 test acc: 97.73681640625\n",
|
||||
"Epoch 50\tTop1 Train accuracy 68.01126098632812\tTop1 Test accuracy: 65.21728515625\tTop5 test acc: 97.76123046875\n",
|
||||
"Epoch 51\tTop1 Train accuracy 68.05032348632812\tTop1 Test accuracy: 65.29052734375\tTop5 test acc: 97.7490234375\n",
|
||||
"Epoch 52\tTop1 Train accuracy 68.05032348632812\tTop1 Test accuracy: 65.3564453125\tTop5 test acc: 97.78564453125\n",
|
||||
"Epoch 53\tTop1 Train accuracy 68.20657348632812\tTop1 Test accuracy: 65.3759765625\tTop5 test acc: 97.7978515625\n",
|
||||
"Epoch 54\tTop1 Train accuracy 68.28469848632812\tTop1 Test accuracy: 65.45654296875\tTop5 test acc: 97.822265625\n",
|
||||
"Epoch 55\tTop1 Train accuracy 68.41912078857422\tTop1 Test accuracy: 65.46875\tTop5 test acc: 97.8466796875\n",
|
||||
"Epoch 56\tTop1 Train accuracy 68.45818328857422\tTop1 Test accuracy: 65.5615234375\tTop5 test acc: 97.85888671875\n",
|
||||
"Epoch 57\tTop1 Train accuracy 68.61443328857422\tTop1 Test accuracy: 65.56640625\tTop5 test acc: 97.87109375\n",
|
||||
"Epoch 58\tTop1 Train accuracy 68.71208953857422\tTop1 Test accuracy: 65.5859375\tTop5 test acc: 97.90771484375\n",
|
||||
"Epoch 59\tTop1 Train accuracy 68.69255828857422\tTop1 Test accuracy: 65.64697265625\tTop5 test acc: 97.919921875\n",
|
||||
"Epoch 60\tTop1 Train accuracy 68.80744934082031\tTop1 Test accuracy: 65.64697265625\tTop5 test acc: 97.93212890625\n",
|
||||
"Epoch 61\tTop1 Train accuracy 68.94416809082031\tTop1 Test accuracy: 65.72021484375\tTop5 test acc: 97.93212890625\n",
|
||||
"Epoch 62\tTop1 Train accuracy 69.04182434082031\tTop1 Test accuracy: 65.76904296875\tTop5 test acc: 97.919921875\n",
|
||||
"Epoch 63\tTop1 Train accuracy 69.06135559082031\tTop1 Test accuracy: 65.84228515625\tTop5 test acc: 97.90771484375\n",
|
||||
"Epoch 64\tTop1 Train accuracy 69.19807434082031\tTop1 Test accuracy: 65.93505859375\tTop5 test acc: 97.90771484375\n",
|
||||
"Epoch 65\tTop1 Train accuracy 69.23713684082031\tTop1 Test accuracy: 65.95947265625\tTop5 test acc: 97.9150390625\n",
|
||||
"Epoch 66\tTop1 Train accuracy 69.25666809082031\tTop1 Test accuracy: 66.0888671875\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 67\tTop1 Train accuracy 69.31526184082031\tTop1 Test accuracy: 66.02783203125\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 68\tTop1 Train accuracy 69.43014526367188\tTop1 Test accuracy: 66.07666015625\tTop5 test acc: 97.9638671875\n",
|
||||
"Epoch 69\tTop1 Train accuracy 69.48873901367188\tTop1 Test accuracy: 66.12060546875\tTop5 test acc: 97.9638671875\n",
|
||||
"Epoch 70\tTop1 Train accuracy 69.50827026367188\tTop1 Test accuracy: 66.083984375\tTop5 test acc: 97.95166015625\n",
|
||||
"Epoch 71\tTop1 Train accuracy 69.60592651367188\tTop1 Test accuracy: 66.1572265625\tTop5 test acc: 97.9638671875\n",
|
||||
"Epoch 72\tTop1 Train accuracy 69.68635559082031\tTop1 Test accuracy: 66.2060546875\tTop5 test acc: 97.95166015625\n",
|
||||
"Epoch 73\tTop1 Train accuracy 69.78170776367188\tTop1 Test accuracy: 66.2744140625\tTop5 test acc: 97.92724609375\n",
|
||||
"Epoch 74\tTop1 Train accuracy 69.84030151367188\tTop1 Test accuracy: 66.31591796875\tTop5 test acc: 97.92724609375\n",
|
||||
"Epoch 75\tTop1 Train accuracy 69.89889526367188\tTop1 Test accuracy: 66.328125\tTop5 test acc: 97.9150390625\n",
|
||||
"Epoch 76\tTop1 Train accuracy 69.93795776367188\tTop1 Test accuracy: 66.41357421875\tTop5 test acc: 97.92724609375\n",
|
||||
"Epoch 77\tTop1 Train accuracy 69.95748901367188\tTop1 Test accuracy: 66.41357421875\tTop5 test acc: 97.9150390625\n",
|
||||
"Epoch 78\tTop1 Train accuracy 70.01608276367188\tTop1 Test accuracy: 66.474609375\tTop5 test acc: 97.9150390625\n",
|
||||
"Epoch 79\tTop1 Train accuracy 69.99655151367188\tTop1 Test accuracy: 66.53564453125\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 80\tTop1 Train accuracy 70.01608276367188\tTop1 Test accuracy: 66.56005859375\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 81\tTop1 Train accuracy 70.09420776367188\tTop1 Test accuracy: 66.56494140625\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 82\tTop1 Train accuracy 70.11373901367188\tTop1 Test accuracy: 66.650390625\tTop5 test acc: 97.939453125\n",
|
||||
"Epoch 83\tTop1 Train accuracy 70.19186401367188\tTop1 Test accuracy: 66.71142578125\tTop5 test acc: 97.92724609375\n",
|
||||
"Epoch 84\tTop1 Train accuracy 70.26998901367188\tTop1 Test accuracy: 66.7236328125\tTop5 test acc: 97.90283203125\n",
|
||||
"Epoch 85\tTop1 Train accuracy 70.32858276367188\tTop1 Test accuracy: 66.73583984375\tTop5 test acc: 97.90283203125\n",
|
||||
"Epoch 86\tTop1 Train accuracy 70.32858276367188\tTop1 Test accuracy: 66.748046875\tTop5 test acc: 97.890625\n",
|
||||
"Epoch 87\tTop1 Train accuracy 70.46530151367188\tTop1 Test accuracy: 66.7724609375\tTop5 test acc: 97.890625\n",
|
||||
"Epoch 88\tTop1 Train accuracy 70.52389526367188\tTop1 Test accuracy: 66.78466796875\tTop5 test acc: 97.90283203125\n",
|
||||
"Epoch 89\tTop1 Train accuracy 70.56295776367188\tTop1 Test accuracy: 66.78466796875\tTop5 test acc: 97.890625\n",
|
||||
"Epoch 90\tTop1 Train accuracy 70.68014526367188\tTop1 Test accuracy: 66.83349609375\tTop5 test acc: 97.87841796875\n",
|
||||
"Epoch 91\tTop1 Train accuracy 70.77780151367188\tTop1 Test accuracy: 66.826171875\tTop5 test acc: 97.87841796875\n",
|
||||
"Epoch 92\tTop1 Train accuracy 70.81686401367188\tTop1 Test accuracy: 66.88720703125\tTop5 test acc: 97.87841796875\n",
|
||||
"Epoch 93\tTop1 Train accuracy 70.85592651367188\tTop1 Test accuracy: 66.8994140625\tTop5 test acc: 97.87841796875\n",
|
||||
"Epoch 94\tTop1 Train accuracy 70.91452026367188\tTop1 Test accuracy: 66.9482421875\tTop5 test acc: 97.890625\n",
|
||||
"Epoch 95\tTop1 Train accuracy 71.03170776367188\tTop1 Test accuracy: 66.98486328125\tTop5 test acc: 97.890625\n",
|
||||
"Epoch 96\tTop1 Train accuracy 71.09030151367188\tTop1 Test accuracy: 67.001953125\tTop5 test acc: 97.91015625\n",
|
||||
"Epoch 97\tTop1 Train accuracy 71.09030151367188\tTop1 Test accuracy: 67.0263671875\tTop5 test acc: 97.91015625\n",
|
||||
"Epoch 98\tTop1 Train accuracy 71.12936401367188\tTop1 Test accuracy: 67.06298828125\tTop5 test acc: 97.89794921875\n",
|
||||
"Epoch 99\tTop1 Train accuracy 71.12936401367188\tTop1 Test accuracy: 67.0751953125\tTop5 test acc: 97.8857421875\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
}
|
||||
|
|
@ -814,7 +814,7 @@
|
|||
"source": [
|
||||
""
|
||||
],
|
||||
"execution_count": 26,
|
||||
"execution_count": 27,
|
||||
"outputs": []
|
||||
}
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in New Issue