Note
Go to the end to download the full example code.
Improved Ensemble parameter-efficiency with Packed-Ensembles¶
This tutorial is adapted from a notebook part of a lecture given at the `Helmholtz AI Conference <https://haicon24.de/>`_ by Sebastian Starke, Peter Steinbach, Gianni Franchi, and Olivier Laurent.
In this notebook will work on the MNIST dataset that was introduced by Corinna Cortes, Christopher J.C. Burges, and later modified by Yann LeCun in the foundational paper:
The MNIST dataset consists of 70 000 images of handwritten digits from 0 to 9. The images are grayscale and 28x28-pixel sized. The task is to classify the images into their respective digits. The dataset can be automatically downloaded using the torchvision library.
In this notebook, we will train a model and an ensemble on this task and evaluate their performance. The performance will consist in the following metrics: - Accuracy: the proportion of correctly classified images, - Brier score: a measure of the quality of the predicted probabilities, - Calibration error: a measure of the calibration of the predicted probabilities, - Negative Log-Likelihood: the value of the loss on the test set.
Throughout this notebook, we abstract the training and evaluation process using PyTorch Lightning and TorchUncertainty.
Similarly to keras for tensorflow, PyTorch Lightning is a high-level interface for PyTorch that simplifies the training and evaluation process using a Trainer. TorchUncertainty is partly built on top of PyTorch Lightning and provides tools to train and evaluate models with uncertainty quantification.
TorchUncertainty includes datamodules that handle the data loading and preprocessing. We don’t use them here for tutorial purposes.
1. Download, instantiate and visualize the datasets¶
The dataset is automatically downloaded using torchvision. We then visualize a few images to see a bit what we are working with.
import torch
import torchvision.transforms as T
# We set the number of epochs to some low value for the sake of time
max_epochs = 2
# Create the transforms for the images
train_transform = T.Compose(
[
T.ToTensor(),
# We perform random cropping as data augmentation
T.RandomCrop(28, padding=4),
# As for the MNIST1d dataset, we normalize the data
T.Normalize((0.1307,), (0.3081,)),
]
)
test_transform = T.Compose(
[
T.Grayscale(num_output_channels=1),
T.ToTensor(),
T.CenterCrop(28),
T.Normalize((0.1307,), (0.3081,)),
]
)
# Download and instantiate the dataset
from torch.utils.data import Subset
from torchvision.datasets import MNIST, FashionMNIST
train_data = MNIST(
root="./data/", download=True, train=True, transform=train_transform
)
test_data = MNIST(root="./data/", train=False, transform=test_transform)
# We only take the first 10k images to have the same number of samples as the test set using torch Subsets
ood_data = Subset(
FashionMNIST(root="./data/", download=True, transform=test_transform),
indices=range(10000),
)
# Create the corresponding dataloaders
from torch.utils.data import DataLoader
train_dl = DataLoader(train_data, batch_size=32, shuffle=True)
test_dl = DataLoader(test_data, batch_size=32, shuffle=False)
ood_dl = DataLoader(ood_data, batch_size=32, shuffle=False)
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz to ./data/FashionMNIST/raw/train-images-idx3-ubyte.gz
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Extracting ./data/FashionMNIST/raw/train-images-idx3-ubyte.gz to ./data/FashionMNIST/raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz to ./data/FashionMNIST/raw/train-labels-idx1-ubyte.gz
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Extracting ./data/FashionMNIST/raw/train-labels-idx1-ubyte.gz to ./data/FashionMNIST/raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz to ./data/FashionMNIST/raw/t10k-images-idx3-ubyte.gz
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Extracting ./data/FashionMNIST/raw/t10k-images-idx3-ubyte.gz to ./data/FashionMNIST/raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz to ./data/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz
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Extracting ./data/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/FashionMNIST/raw
You could replace all this cell by simply loading the MNIST datamodule from TorchUncertainty. Now, let’s visualize a few images from the dataset. For this task, we use the viz_data dataset that applies no transformation to the images.
# Datasets without transformation to visualize the unchanged data
viz_data = MNIST(root="./data/", train=False)
ood_viz_data = FashionMNIST(root="./data/", download=True)
print("In distribution data:")
viz_data[0][0]
In distribution data:
<PIL.Image.Image image mode=L size=28x28 at 0x7F63290AE290>
print("Out of distribution data:")
ood_viz_data[0][0]
Out of distribution data:
<PIL.Image.Image image mode=L size=28x28 at 0x7F63290ACDF0>
2. Create & train the model¶
We will create a simple convolutional neural network (CNN): the LeNet model (also introduced by LeCun).
import torch.nn as nn
import torch.nn.functional as F
class LeNet(nn.Module):
def __init__(
self,
in_channels: int,
num_classes: int,
) -> None:
super().__init__()
self.conv1 = nn.Conv2d(in_channels, 6, (5, 5))
self.conv2 = nn.Conv2d(6, 16, (5, 5))
self.pooling = nn.AdaptiveAvgPool2d((4, 4))
self.fc1 = nn.Linear(256, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, num_classes)
def forward(self, x: torch.Tensor) -> torch.Tensor:
out = F.relu(self.conv1(x))
out = F.max_pool2d(out, 2)
out = F.relu(self.conv2(out))
out = F.max_pool2d(out, 2)
out = torch.flatten(out, 1)
out = F.relu(self.fc1(out))
out = F.relu(self.fc2(out))
return self.fc3(out) # No softmax in the model!
# Instantiate the model, the images are in grayscale so the number of channels is 1
model = LeNet(in_channels=1, num_classes=10)
We now need to define the optimization recipe: - the optimizer, here the standard stochastic gradient descent (SGD) with a learning rate of 0.05 - the scheduler, here cosine annealing.
def optim_recipe(model, lr_mult: float = 1.0):
optimizer = torch.optim.SGD(model.parameters(), lr=0.05 * lr_mult)
scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=10)
return {"optimizer": optimizer, "scheduler": scheduler}
To train the model, we use TorchUncertainty, a library that we have developed to ease the training and evaluation of models with uncertainty.
Note: To train supervised classification models we most often use the cross-entropy loss. With weight-decay, minimizing this loss amounts to finding a Maximum a posteriori (MAP) estimate of the model parameters. This means that the model is trained to predict the most likely class for each input.
from torch_uncertainty.routines import ClassificationRoutine
from torch_uncertainty import TUTrainer
# Create the trainer that will handle the training
trainer = TUTrainer(accelerator="cpu", max_epochs=max_epochs)
# The routine is a wrapper of the model that contains the training logic with the metrics, etc
routine = ClassificationRoutine(
num_classes=10,
model=model,
loss=nn.CrossEntropyLoss(),
optim_recipe=optim_recipe(model),
eval_ood=True,
)
# In practice, avoid performing the validation on the test set (if you do model selection)
trainer.fit(routine, train_dataloaders=train_dl, val_dataloaders=test_dl)
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Epoch 0: 3%|▎ | 52/1875 [00:00<00:23, 76.46it/s, v_num=10, train_loss=2.300]
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Epoch 0: 3%|▎ | 54/1875 [00:00<00:23, 76.44it/s, v_num=10, train_loss=2.290]
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Epoch 0: 3%|▎ | 57/1875 [00:00<00:23, 76.46it/s, v_num=10, train_loss=2.280]
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Epoch 0: 4%|▎ | 69/1875 [00:00<00:23, 76.69it/s, v_num=10, train_loss=2.320]
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Epoch 0: 4%|▍ | 71/1875 [00:00<00:23, 76.73it/s, v_num=10, train_loss=2.280]
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Epoch 0: 4%|▍ | 80/1875 [00:01<00:23, 76.55it/s, v_num=10, train_loss=2.310]
Epoch 0: 4%|▍ | 81/1875 [00:01<00:23, 76.56it/s, v_num=10, train_loss=2.310]
Epoch 0: 4%|▍ | 81/1875 [00:01<00:23, 76.54it/s, v_num=10, train_loss=2.290]
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Epoch 0: 5%|▍ | 88/1875 [00:01<00:23, 76.62it/s, v_num=10, train_loss=2.260]
Epoch 0: 5%|▍ | 88/1875 [00:01<00:23, 76.60it/s, v_num=10, train_loss=2.240]
Epoch 0: 5%|▍ | 89/1875 [00:01<00:23, 76.63it/s, v_num=10, train_loss=2.240]
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Epoch 0: 5%|▍ | 90/1875 [00:01<00:23, 76.65it/s, v_num=10, train_loss=2.290]
Epoch 0: 5%|▍ | 90/1875 [00:01<00:23, 76.64it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▍ | 91/1875 [00:01<00:23, 76.66it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▍ | 91/1875 [00:01<00:23, 76.64it/s, v_num=10, train_loss=2.310]
Epoch 0: 5%|▍ | 92/1875 [00:01<00:23, 76.67it/s, v_num=10, train_loss=2.310]
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Epoch 0: 5%|▍ | 93/1875 [00:01<00:23, 76.66it/s, v_num=10, train_loss=2.300]
Epoch 0: 5%|▌ | 94/1875 [00:01<00:23, 76.67it/s, v_num=10, train_loss=2.300]
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Epoch 0: 5%|▌ | 95/1875 [00:01<00:23, 76.67it/s, v_num=10, train_loss=2.280]
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Epoch 0: 5%|▌ | 96/1875 [00:01<00:23, 76.68it/s, v_num=10, train_loss=2.290]
Epoch 0: 5%|▌ | 96/1875 [00:01<00:23, 76.66it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▌ | 97/1875 [00:01<00:23, 76.69it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▌ | 97/1875 [00:01<00:23, 76.67it/s, v_num=10, train_loss=2.250]
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Epoch 0: 5%|▌ | 99/1875 [00:01<00:23, 76.70it/s, v_num=10, train_loss=2.270]
Epoch 0: 5%|▌ | 99/1875 [00:01<00:23, 76.69it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▌ | 100/1875 [00:01<00:23, 76.72it/s, v_num=10, train_loss=2.280]
Epoch 0: 5%|▌ | 100/1875 [00:01<00:23, 76.71it/s, v_num=10, train_loss=2.290]
Epoch 0: 5%|▌ | 101/1875 [00:01<00:23, 76.69it/s, v_num=10, train_loss=2.290]
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Epoch 0: 6%|▌ | 105/1875 [00:01<00:23, 76.71it/s, v_num=10, train_loss=2.270]
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Epoch 0: 6%|▌ | 106/1875 [00:01<00:23, 76.72it/s, v_num=10, train_loss=2.280]
Epoch 0: 6%|▌ | 106/1875 [00:01<00:23, 76.71it/s, v_num=10, train_loss=2.270]
Epoch 0: 6%|▌ | 107/1875 [00:01<00:23, 76.73it/s, v_num=10, train_loss=2.270]
Epoch 0: 6%|▌ | 107/1875 [00:01<00:23, 76.72it/s, v_num=10, train_loss=2.280]
Epoch 0: 6%|▌ | 108/1875 [00:01<00:23, 76.74it/s, v_num=10, train_loss=2.280]
Epoch 0: 6%|▌ | 108/1875 [00:01<00:23, 76.73it/s, v_num=10, train_loss=2.280]
Epoch 0: 6%|▌ | 109/1875 [00:01<00:23, 76.74it/s, v_num=10, train_loss=2.280]
Epoch 0: 6%|▌ | 109/1875 [00:01<00:23, 76.72it/s, v_num=10, train_loss=2.230]
Epoch 0: 6%|▌ | 110/1875 [00:01<00:22, 76.74it/s, v_num=10, train_loss=2.230]
Epoch 0: 6%|▌ | 110/1875 [00:01<00:23, 76.73it/s, v_num=10, train_loss=2.250]
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Epoch 0: 6%|▌ | 112/1875 [00:01<00:22, 76.73it/s, v_num=10, train_loss=2.260]
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Epoch 0: 6%|▌ | 113/1875 [00:01<00:22, 76.73it/s, v_num=10, train_loss=2.240]
Epoch 0: 6%|▌ | 114/1875 [00:01<00:22, 76.76it/s, v_num=10, train_loss=2.240]
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Epoch 0: 6%|▌ | 115/1875 [00:01<00:22, 76.77it/s, v_num=10, train_loss=2.260]
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Epoch 0: 6%|▌ | 117/1875 [00:01<00:22, 76.73it/s, v_num=10, train_loss=2.250]
Epoch 0: 6%|▌ | 117/1875 [00:01<00:22, 76.72it/s, v_num=10, train_loss=2.230]
Epoch 0: 6%|▋ | 118/1875 [00:01<00:22, 76.74it/s, v_num=10, train_loss=2.230]
Epoch 0: 6%|▋ | 118/1875 [00:01<00:22, 76.72it/s, v_num=10, train_loss=2.210]
Epoch 0: 6%|▋ | 119/1875 [00:01<00:22, 76.74it/s, v_num=10, train_loss=2.210]
Epoch 0: 6%|▋ | 119/1875 [00:01<00:22, 76.72it/s, v_num=10, train_loss=2.200]
Epoch 0: 6%|▋ | 120/1875 [00:01<00:22, 76.74it/s, v_num=10, train_loss=2.200]
Epoch 0: 6%|▋ | 120/1875 [00:01<00:22, 76.73it/s, v_num=10, train_loss=2.220]
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Epoch 0: 7%|▋ | 122/1875 [00:01<00:22, 76.74it/s, v_num=10, train_loss=2.180]
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Epoch 0: 7%|▋ | 125/1875 [00:01<00:22, 76.77it/s, v_num=10, train_loss=2.200]
Epoch 0: 7%|▋ | 125/1875 [00:01<00:22, 76.76it/s, v_num=10, train_loss=2.190]
Epoch 0: 7%|▋ | 126/1875 [00:01<00:22, 76.78it/s, v_num=10, train_loss=2.190]
Epoch 0: 7%|▋ | 126/1875 [00:01<00:22, 76.77it/s, v_num=10, train_loss=2.210]
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Epoch 0: 97%|█████████▋| 1820/1875 [00:23<00:00, 76.94it/s, v_num=10, train_loss=0.175]
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Epoch 1: 2%|▏ | 34/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.231, Acc%=97.00]
Epoch 1: 2%|▏ | 35/1875 [00:00<00:23, 77.19it/s, v_num=10, train_loss=0.231, Acc%=97.00]
Epoch 1: 2%|▏ | 35/1875 [00:00<00:23, 77.15it/s, v_num=10, train_loss=0.0519, Acc%=97.00]
Epoch 1: 2%|▏ | 36/1875 [00:00<00:23, 77.20it/s, v_num=10, train_loss=0.0519, Acc%=97.00]
Epoch 1: 2%|▏ | 36/1875 [00:00<00:23, 77.15it/s, v_num=10, train_loss=0.154, Acc%=97.00]
Epoch 1: 2%|▏ | 37/1875 [00:00<00:23, 77.17it/s, v_num=10, train_loss=0.154, Acc%=97.00]
Epoch 1: 2%|▏ | 37/1875 [00:00<00:23, 77.13it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 2%|▏ | 38/1875 [00:00<00:23, 77.14it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 2%|▏ | 38/1875 [00:00<00:23, 77.10it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 2%|▏ | 39/1875 [00:00<00:23, 77.15it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 2%|▏ | 39/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.167, Acc%=97.00]
Epoch 1: 2%|▏ | 40/1875 [00:00<00:23, 77.16it/s, v_num=10, train_loss=0.167, Acc%=97.00]
Epoch 1: 2%|▏ | 40/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.321, Acc%=97.00]
Epoch 1: 2%|▏ | 41/1875 [00:00<00:23, 77.18it/s, v_num=10, train_loss=0.321, Acc%=97.00]
Epoch 1: 2%|▏ | 41/1875 [00:00<00:23, 77.14it/s, v_num=10, train_loss=0.175, Acc%=97.00]
Epoch 1: 2%|▏ | 42/1875 [00:00<00:23, 77.16it/s, v_num=10, train_loss=0.175, Acc%=97.00]
Epoch 1: 2%|▏ | 42/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.0704, Acc%=97.00]
Epoch 1: 2%|▏ | 43/1875 [00:00<00:23, 77.14it/s, v_num=10, train_loss=0.0704, Acc%=97.00]
Epoch 1: 2%|▏ | 43/1875 [00:00<00:23, 77.11it/s, v_num=10, train_loss=0.0732, Acc%=97.00]
Epoch 1: 2%|▏ | 44/1875 [00:00<00:23, 77.13it/s, v_num=10, train_loss=0.0732, Acc%=97.00]
Epoch 1: 2%|▏ | 44/1875 [00:00<00:23, 77.09it/s, v_num=10, train_loss=0.209, Acc%=97.00]
Epoch 1: 2%|▏ | 45/1875 [00:00<00:23, 77.11it/s, v_num=10, train_loss=0.209, Acc%=97.00]
Epoch 1: 2%|▏ | 45/1875 [00:00<00:23, 77.08it/s, v_num=10, train_loss=0.167, Acc%=97.00]
Epoch 1: 2%|▏ | 46/1875 [00:00<00:23, 77.11it/s, v_num=10, train_loss=0.167, Acc%=97.00]
Epoch 1: 2%|▏ | 46/1875 [00:00<00:23, 77.07it/s, v_num=10, train_loss=0.388, Acc%=97.00]
Epoch 1: 3%|▎ | 47/1875 [00:00<00:23, 77.11it/s, v_num=10, train_loss=0.388, Acc%=97.00]
Epoch 1: 3%|▎ | 47/1875 [00:00<00:23, 77.08it/s, v_num=10, train_loss=0.598, Acc%=97.00]
Epoch 1: 3%|▎ | 48/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.598, Acc%=97.00]
Epoch 1: 3%|▎ | 48/1875 [00:00<00:23, 77.10it/s, v_num=10, train_loss=0.496, Acc%=97.00]
Epoch 1: 3%|▎ | 49/1875 [00:00<00:23, 77.15it/s, v_num=10, train_loss=0.496, Acc%=97.00]
Epoch 1: 3%|▎ | 49/1875 [00:00<00:23, 77.12it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 3%|▎ | 50/1875 [00:00<00:23, 77.17it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 3%|▎ | 50/1875 [00:00<00:23, 77.14it/s, v_num=10, train_loss=0.326, Acc%=97.00]
Epoch 1: 3%|▎ | 51/1875 [00:00<00:23, 77.19it/s, v_num=10, train_loss=0.326, Acc%=97.00]
Epoch 1: 3%|▎ | 51/1875 [00:00<00:23, 77.16it/s, v_num=10, train_loss=0.205, Acc%=97.00]
Epoch 1: 3%|▎ | 52/1875 [00:00<00:23, 77.22it/s, v_num=10, train_loss=0.205, Acc%=97.00]
Epoch 1: 3%|▎ | 52/1875 [00:00<00:23, 77.19it/s, v_num=10, train_loss=0.084, Acc%=97.00]
Epoch 1: 3%|▎ | 53/1875 [00:00<00:23, 77.23it/s, v_num=10, train_loss=0.084, Acc%=97.00]
Epoch 1: 3%|▎ | 53/1875 [00:00<00:23, 77.21it/s, v_num=10, train_loss=0.0799, Acc%=97.00]
Epoch 1: 3%|▎ | 54/1875 [00:00<00:23, 77.23it/s, v_num=10, train_loss=0.0799, Acc%=97.00]
Epoch 1: 3%|▎ | 54/1875 [00:00<00:23, 77.20it/s, v_num=10, train_loss=0.0433, Acc%=97.00]
Epoch 1: 3%|▎ | 55/1875 [00:00<00:23, 77.21it/s, v_num=10, train_loss=0.0433, Acc%=97.00]
Epoch 1: 3%|▎ | 55/1875 [00:00<00:23, 77.18it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 3%|▎ | 56/1875 [00:00<00:23, 77.22it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 3%|▎ | 56/1875 [00:00<00:23, 77.19it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 3%|▎ | 57/1875 [00:00<00:23, 77.23it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 3%|▎ | 57/1875 [00:00<00:23, 77.20it/s, v_num=10, train_loss=0.125, Acc%=97.00]
Epoch 1: 3%|▎ | 58/1875 [00:00<00:23, 77.22it/s, v_num=10, train_loss=0.125, Acc%=97.00]
Epoch 1: 3%|▎ | 58/1875 [00:00<00:23, 77.20it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 3%|▎ | 59/1875 [00:00<00:23, 77.24it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 3%|▎ | 59/1875 [00:00<00:23, 77.22it/s, v_num=10, train_loss=0.086, Acc%=97.00]
Epoch 1: 3%|▎ | 60/1875 [00:00<00:23, 77.27it/s, v_num=10, train_loss=0.086, Acc%=97.00]
Epoch 1: 3%|▎ | 60/1875 [00:00<00:23, 77.25it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 3%|▎ | 61/1875 [00:00<00:23, 77.29it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 3%|▎ | 61/1875 [00:00<00:23, 77.27it/s, v_num=10, train_loss=0.177, Acc%=97.00]
Epoch 1: 3%|▎ | 62/1875 [00:00<00:23, 77.32it/s, v_num=10, train_loss=0.177, Acc%=97.00]
Epoch 1: 3%|▎ | 62/1875 [00:00<00:23, 77.30it/s, v_num=10, train_loss=0.163, Acc%=97.00]
Epoch 1: 3%|▎ | 63/1875 [00:00<00:23, 77.33it/s, v_num=10, train_loss=0.163, Acc%=97.00]
Epoch 1: 3%|▎ | 63/1875 [00:00<00:23, 77.31it/s, v_num=10, train_loss=0.0699, Acc%=97.00]
Epoch 1: 3%|▎ | 64/1875 [00:00<00:23, 77.34it/s, v_num=10, train_loss=0.0699, Acc%=97.00]
Epoch 1: 3%|▎ | 64/1875 [00:00<00:23, 77.32it/s, v_num=10, train_loss=0.233, Acc%=97.00]
Epoch 1: 3%|▎ | 65/1875 [00:00<00:23, 77.34it/s, v_num=10, train_loss=0.233, Acc%=97.00]
Epoch 1: 3%|▎ | 65/1875 [00:00<00:23, 77.32it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 4%|▎ | 66/1875 [00:00<00:23, 77.33it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 4%|▎ | 66/1875 [00:00<00:23, 77.30it/s, v_num=10, train_loss=0.0565, Acc%=97.00]
Epoch 1: 4%|▎ | 67/1875 [00:00<00:23, 77.33it/s, v_num=10, train_loss=0.0565, Acc%=97.00]
Epoch 1: 4%|▎ | 67/1875 [00:00<00:23, 77.31it/s, v_num=10, train_loss=0.041, Acc%=97.00]
Epoch 1: 4%|▎ | 68/1875 [00:00<00:23, 77.35it/s, v_num=10, train_loss=0.041, Acc%=97.00]
Epoch 1: 4%|▎ | 68/1875 [00:00<00:23, 77.33it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 4%|▎ | 69/1875 [00:00<00:23, 77.37it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 4%|▎ | 69/1875 [00:00<00:23, 77.35it/s, v_num=10, train_loss=0.0591, Acc%=97.00]
Epoch 1: 4%|▎ | 70/1875 [00:00<00:23, 77.36it/s, v_num=10, train_loss=0.0591, Acc%=97.00]
Epoch 1: 4%|▎ | 70/1875 [00:00<00:23, 77.34it/s, v_num=10, train_loss=0.0402, Acc%=97.00]
Epoch 1: 4%|▍ | 71/1875 [00:00<00:23, 77.36it/s, v_num=10, train_loss=0.0402, Acc%=97.00]
Epoch 1: 4%|▍ | 71/1875 [00:00<00:23, 77.33it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 4%|▍ | 72/1875 [00:00<00:23, 77.32it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 4%|▍ | 72/1875 [00:00<00:23, 77.29it/s, v_num=10, train_loss=0.161, Acc%=97.00]
Epoch 1: 4%|▍ | 73/1875 [00:00<00:23, 77.28it/s, v_num=10, train_loss=0.161, Acc%=97.00]
Epoch 1: 4%|▍ | 73/1875 [00:00<00:23, 77.25it/s, v_num=10, train_loss=0.202, Acc%=97.00]
Epoch 1: 4%|▍ | 74/1875 [00:00<00:23, 77.26it/s, v_num=10, train_loss=0.202, Acc%=97.00]
Epoch 1: 4%|▍ | 74/1875 [00:00<00:23, 77.25it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 4%|▍ | 75/1875 [00:00<00:23, 77.26it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 4%|▍ | 75/1875 [00:00<00:23, 77.24it/s, v_num=10, train_loss=0.0189, Acc%=97.00]
Epoch 1: 4%|▍ | 76/1875 [00:00<00:23, 77.22it/s, v_num=10, train_loss=0.0189, Acc%=97.00]
Epoch 1: 4%|▍ | 76/1875 [00:00<00:23, 77.20it/s, v_num=10, train_loss=0.180, Acc%=97.00]
Epoch 1: 4%|▍ | 77/1875 [00:00<00:23, 77.21it/s, v_num=10, train_loss=0.180, Acc%=97.00]
Epoch 1: 4%|▍ | 77/1875 [00:00<00:23, 77.19it/s, v_num=10, train_loss=0.0444, Acc%=97.00]
Epoch 1: 4%|▍ | 78/1875 [00:01<00:23, 77.22it/s, v_num=10, train_loss=0.0444, Acc%=97.00]
Epoch 1: 4%|▍ | 78/1875 [00:01<00:23, 77.20it/s, v_num=10, train_loss=0.303, Acc%=97.00]
Epoch 1: 4%|▍ | 79/1875 [00:01<00:23, 77.22it/s, v_num=10, train_loss=0.303, Acc%=97.00]
Epoch 1: 4%|▍ | 79/1875 [00:01<00:23, 77.20it/s, v_num=10, train_loss=0.183, Acc%=97.00]
Epoch 1: 4%|▍ | 80/1875 [00:01<00:23, 77.23it/s, v_num=10, train_loss=0.183, Acc%=97.00]
Epoch 1: 4%|▍ | 80/1875 [00:01<00:23, 77.21it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 4%|▍ | 81/1875 [00:01<00:23, 77.23it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 4%|▍ | 81/1875 [00:01<00:23, 77.21it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 4%|▍ | 82/1875 [00:01<00:23, 77.23it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 4%|▍ | 82/1875 [00:01<00:23, 77.21it/s, v_num=10, train_loss=0.995, Acc%=97.00]
Epoch 1: 4%|▍ | 83/1875 [00:01<00:23, 77.21it/s, v_num=10, train_loss=0.995, Acc%=97.00]
Epoch 1: 4%|▍ | 83/1875 [00:01<00:23, 77.19it/s, v_num=10, train_loss=0.0372, Acc%=97.00]
Epoch 1: 4%|▍ | 84/1875 [00:01<00:23, 77.18it/s, v_num=10, train_loss=0.0372, Acc%=97.00]
Epoch 1: 4%|▍ | 84/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.0561, Acc%=97.00]
Epoch 1: 5%|▍ | 85/1875 [00:01<00:23, 77.17it/s, v_num=10, train_loss=0.0561, Acc%=97.00]
Epoch 1: 5%|▍ | 85/1875 [00:01<00:23, 77.15it/s, v_num=10, train_loss=0.0793, Acc%=97.00]
Epoch 1: 5%|▍ | 86/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.0793, Acc%=97.00]
Epoch 1: 5%|▍ | 86/1875 [00:01<00:23, 77.14it/s, v_num=10, train_loss=0.0187, Acc%=97.00]
Epoch 1: 5%|▍ | 87/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.0187, Acc%=97.00]
Epoch 1: 5%|▍ | 87/1875 [00:01<00:23, 77.15it/s, v_num=10, train_loss=0.0867, Acc%=97.00]
Epoch 1: 5%|▍ | 88/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.0867, Acc%=97.00]
Epoch 1: 5%|▍ | 88/1875 [00:01<00:23, 77.14it/s, v_num=10, train_loss=0.140, Acc%=97.00]
Epoch 1: 5%|▍ | 89/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.140, Acc%=97.00]
Epoch 1: 5%|▍ | 89/1875 [00:01<00:23, 77.15it/s, v_num=10, train_loss=0.244, Acc%=97.00]
Epoch 1: 5%|▍ | 90/1875 [00:01<00:23, 77.17it/s, v_num=10, train_loss=0.244, Acc%=97.00]
Epoch 1: 5%|▍ | 90/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.102, Acc%=97.00]
Epoch 1: 5%|▍ | 91/1875 [00:01<00:23, 77.18it/s, v_num=10, train_loss=0.102, Acc%=97.00]
Epoch 1: 5%|▍ | 91/1875 [00:01<00:23, 77.16it/s, v_num=10, train_loss=0.631, Acc%=97.00]
Epoch 1: 5%|▍ | 92/1875 [00:01<00:23, 77.19it/s, v_num=10, train_loss=0.631, Acc%=97.00]
Epoch 1: 5%|▍ | 92/1875 [00:01<00:23, 77.18it/s, v_num=10, train_loss=0.0939, Acc%=97.00]
Epoch 1: 5%|▍ | 93/1875 [00:01<00:23, 77.21it/s, v_num=10, train_loss=0.0939, Acc%=97.00]
Epoch 1: 5%|▍ | 93/1875 [00:01<00:23, 77.20it/s, v_num=10, train_loss=0.306, Acc%=97.00]
Epoch 1: 5%|▌ | 94/1875 [00:01<00:23, 77.23it/s, v_num=10, train_loss=0.306, Acc%=97.00]
Epoch 1: 5%|▌ | 94/1875 [00:01<00:23, 77.22it/s, v_num=10, train_loss=0.0917, Acc%=97.00]
Epoch 1: 5%|▌ | 95/1875 [00:01<00:23, 77.25it/s, v_num=10, train_loss=0.0917, Acc%=97.00]
Epoch 1: 5%|▌ | 95/1875 [00:01<00:23, 77.24it/s, v_num=10, train_loss=0.394, Acc%=97.00]
Epoch 1: 5%|▌ | 96/1875 [00:01<00:23, 77.27it/s, v_num=10, train_loss=0.394, Acc%=97.00]
Epoch 1: 5%|▌ | 96/1875 [00:01<00:23, 77.25it/s, v_num=10, train_loss=0.0665, Acc%=97.00]
Epoch 1: 5%|▌ | 97/1875 [00:01<00:23, 77.28it/s, v_num=10, train_loss=0.0665, Acc%=97.00]
Epoch 1: 5%|▌ | 97/1875 [00:01<00:23, 77.27it/s, v_num=10, train_loss=0.0767, Acc%=97.00]
Epoch 1: 5%|▌ | 98/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.0767, Acc%=97.00]
Epoch 1: 5%|▌ | 98/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.250, Acc%=97.00]
Epoch 1: 5%|▌ | 99/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.250, Acc%=97.00]
Epoch 1: 5%|▌ | 99/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.110, Acc%=97.00]
Epoch 1: 5%|▌ | 100/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.110, Acc%=97.00]
Epoch 1: 5%|▌ | 100/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 5%|▌ | 101/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 5%|▌ | 101/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.200, Acc%=97.00]
Epoch 1: 5%|▌ | 102/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.200, Acc%=97.00]
Epoch 1: 5%|▌ | 102/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.0334, Acc%=97.00]
Epoch 1: 5%|▌ | 103/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.0334, Acc%=97.00]
Epoch 1: 5%|▌ | 103/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.361, Acc%=97.00]
Epoch 1: 6%|▌ | 104/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.361, Acc%=97.00]
Epoch 1: 6%|▌ | 104/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.236, Acc%=97.00]
Epoch 1: 6%|▌ | 105/1875 [00:01<00:22, 77.35it/s, v_num=10, train_loss=0.236, Acc%=97.00]
Epoch 1: 6%|▌ | 105/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 6%|▌ | 106/1875 [00:01<00:22, 77.36it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 6%|▌ | 106/1875 [00:01<00:22, 77.35it/s, v_num=10, train_loss=0.049, Acc%=97.00]
Epoch 1: 6%|▌ | 107/1875 [00:01<00:22, 77.37it/s, v_num=10, train_loss=0.049, Acc%=97.00]
Epoch 1: 6%|▌ | 107/1875 [00:01<00:22, 77.36it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 6%|▌ | 108/1875 [00:01<00:22, 77.39it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 6%|▌ | 108/1875 [00:01<00:22, 77.38it/s, v_num=10, train_loss=0.094, Acc%=97.00]
Epoch 1: 6%|▌ | 109/1875 [00:01<00:22, 77.41it/s, v_num=10, train_loss=0.094, Acc%=97.00]
Epoch 1: 6%|▌ | 109/1875 [00:01<00:22, 77.39it/s, v_num=10, train_loss=0.258, Acc%=97.00]
Epoch 1: 6%|▌ | 110/1875 [00:01<00:22, 77.42it/s, v_num=10, train_loss=0.258, Acc%=97.00]
Epoch 1: 6%|▌ | 110/1875 [00:01<00:22, 77.41it/s, v_num=10, train_loss=0.547, Acc%=97.00]
Epoch 1: 6%|▌ | 111/1875 [00:01<00:22, 77.44it/s, v_num=10, train_loss=0.547, Acc%=97.00]
Epoch 1: 6%|▌ | 111/1875 [00:01<00:22, 77.43it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 6%|▌ | 112/1875 [00:01<00:22, 77.45it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 6%|▌ | 112/1875 [00:01<00:22, 77.44it/s, v_num=10, train_loss=0.183, Acc%=97.00]
Epoch 1: 6%|▌ | 113/1875 [00:01<00:22, 77.46it/s, v_num=10, train_loss=0.183, Acc%=97.00]
Epoch 1: 6%|▌ | 113/1875 [00:01<00:22, 77.45it/s, v_num=10, train_loss=0.287, Acc%=97.00]
Epoch 1: 6%|▌ | 114/1875 [00:01<00:22, 77.48it/s, v_num=10, train_loss=0.287, Acc%=97.00]
Epoch 1: 6%|▌ | 114/1875 [00:01<00:22, 77.46it/s, v_num=10, train_loss=0.157, Acc%=97.00]
Epoch 1: 6%|▌ | 115/1875 [00:01<00:22, 77.48it/s, v_num=10, train_loss=0.157, Acc%=97.00]
Epoch 1: 6%|▌ | 115/1875 [00:01<00:22, 77.47it/s, v_num=10, train_loss=0.0657, Acc%=97.00]
Epoch 1: 6%|▌ | 116/1875 [00:01<00:22, 77.49it/s, v_num=10, train_loss=0.0657, Acc%=97.00]
Epoch 1: 6%|▌ | 116/1875 [00:01<00:22, 77.48it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 6%|▌ | 117/1875 [00:01<00:22, 77.50it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 6%|▌ | 117/1875 [00:01<00:22, 77.49it/s, v_num=10, train_loss=0.422, Acc%=97.00]
Epoch 1: 6%|▋ | 118/1875 [00:01<00:22, 77.51it/s, v_num=10, train_loss=0.422, Acc%=97.00]
Epoch 1: 6%|▋ | 118/1875 [00:01<00:22, 77.50it/s, v_num=10, train_loss=0.322, Acc%=97.00]
Epoch 1: 6%|▋ | 119/1875 [00:01<00:22, 77.50it/s, v_num=10, train_loss=0.322, Acc%=97.00]
Epoch 1: 6%|▋ | 119/1875 [00:01<00:22, 77.49it/s, v_num=10, train_loss=0.0356, Acc%=97.00]
Epoch 1: 6%|▋ | 120/1875 [00:01<00:22, 77.42it/s, v_num=10, train_loss=0.0356, Acc%=97.00]
Epoch 1: 6%|▋ | 120/1875 [00:01<00:22, 77.41it/s, v_num=10, train_loss=0.264, Acc%=97.00]
Epoch 1: 6%|▋ | 121/1875 [00:01<00:22, 77.42it/s, v_num=10, train_loss=0.264, Acc%=97.00]
Epoch 1: 6%|▋ | 121/1875 [00:01<00:22, 77.40it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 7%|▋ | 122/1875 [00:01<00:22, 77.41it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 7%|▋ | 122/1875 [00:01<00:22, 77.40it/s, v_num=10, train_loss=0.296, Acc%=97.00]
Epoch 1: 7%|▋ | 123/1875 [00:01<00:22, 77.39it/s, v_num=10, train_loss=0.296, Acc%=97.00]
Epoch 1: 7%|▋ | 123/1875 [00:01<00:22, 77.38it/s, v_num=10, train_loss=0.0291, Acc%=97.00]
Epoch 1: 7%|▋ | 124/1875 [00:01<00:22, 77.39it/s, v_num=10, train_loss=0.0291, Acc%=97.00]
Epoch 1: 7%|▋ | 124/1875 [00:01<00:22, 77.38it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 7%|▋ | 125/1875 [00:01<00:22, 77.38it/s, v_num=10, train_loss=0.162, Acc%=97.00]
Epoch 1: 7%|▋ | 125/1875 [00:01<00:22, 77.37it/s, v_num=10, train_loss=0.307, Acc%=97.00]
Epoch 1: 7%|▋ | 126/1875 [00:01<00:22, 77.35it/s, v_num=10, train_loss=0.307, Acc%=97.00]
Epoch 1: 7%|▋ | 126/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 7%|▋ | 127/1875 [00:01<00:22, 77.35it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 7%|▋ | 127/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.0734, Acc%=97.00]
Epoch 1: 7%|▋ | 128/1875 [00:01<00:22, 77.34it/s, v_num=10, train_loss=0.0734, Acc%=97.00]
Epoch 1: 7%|▋ | 128/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.460, Acc%=97.00]
Epoch 1: 7%|▋ | 129/1875 [00:01<00:22, 77.33it/s, v_num=10, train_loss=0.460, Acc%=97.00]
Epoch 1: 7%|▋ | 129/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.0507, Acc%=97.00]
Epoch 1: 7%|▋ | 130/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.0507, Acc%=97.00]
Epoch 1: 7%|▋ | 130/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.245, Acc%=97.00]
Epoch 1: 7%|▋ | 131/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.245, Acc%=97.00]
Epoch 1: 7%|▋ | 131/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.0443, Acc%=97.00]
Epoch 1: 7%|▋ | 132/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.0443, Acc%=97.00]
Epoch 1: 7%|▋ | 132/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.142, Acc%=97.00]
Epoch 1: 7%|▋ | 133/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.142, Acc%=97.00]
Epoch 1: 7%|▋ | 133/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.106, Acc%=97.00]
Epoch 1: 7%|▋ | 134/1875 [00:01<00:22, 77.32it/s, v_num=10, train_loss=0.106, Acc%=97.00]
Epoch 1: 7%|▋ | 134/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 7%|▋ | 135/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 7%|▋ | 135/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.267, Acc%=97.00]
Epoch 1: 7%|▋ | 136/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.267, Acc%=97.00]
Epoch 1: 7%|▋ | 136/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.207, Acc%=97.00]
Epoch 1: 7%|▋ | 137/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.207, Acc%=97.00]
Epoch 1: 7%|▋ | 137/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.278, Acc%=97.00]
Epoch 1: 7%|▋ | 138/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.278, Acc%=97.00]
Epoch 1: 7%|▋ | 138/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.0914, Acc%=97.00]
Epoch 1: 7%|▋ | 139/1875 [00:01<00:22, 77.31it/s, v_num=10, train_loss=0.0914, Acc%=97.00]
Epoch 1: 7%|▋ | 139/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.185, Acc%=97.00]
Epoch 1: 7%|▋ | 140/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.185, Acc%=97.00]
Epoch 1: 7%|▋ | 140/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 8%|▊ | 141/1875 [00:01<00:22, 77.30it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 8%|▊ | 141/1875 [00:01<00:22, 77.29it/s, v_num=10, train_loss=0.177, Acc%=97.00]
Epoch 1: 8%|▊ | 142/1875 [00:01<00:22, 77.25it/s, v_num=10, train_loss=0.177, Acc%=97.00]
Epoch 1: 8%|▊ | 142/1875 [00:01<00:22, 77.24it/s, v_num=10, train_loss=0.294, Acc%=97.00]
Epoch 1: 8%|▊ | 143/1875 [00:01<00:22, 77.26it/s, v_num=10, train_loss=0.294, Acc%=97.00]
Epoch 1: 8%|▊ | 143/1875 [00:01<00:22, 77.25it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 8%|▊ | 144/1875 [00:01<00:22, 77.11it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 8%|▊ | 144/1875 [00:01<00:22, 77.10it/s, v_num=10, train_loss=0.257, Acc%=97.00]
Epoch 1: 8%|▊ | 145/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.257, Acc%=97.00]
Epoch 1: 8%|▊ | 145/1875 [00:01<00:22, 77.05it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 8%|▊ | 146/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 8%|▊ | 146/1875 [00:01<00:22, 77.05it/s, v_num=10, train_loss=0.275, Acc%=97.00]
Epoch 1: 8%|▊ | 147/1875 [00:01<00:22, 77.07it/s, v_num=10, train_loss=0.275, Acc%=97.00]
Epoch 1: 8%|▊ | 147/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.0518, Acc%=97.00]
Epoch 1: 8%|▊ | 148/1875 [00:01<00:22, 77.07it/s, v_num=10, train_loss=0.0518, Acc%=97.00]
Epoch 1: 8%|▊ | 148/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 8%|▊ | 149/1875 [00:01<00:22, 77.07it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 8%|▊ | 149/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.0678, Acc%=97.00]
Epoch 1: 8%|▊ | 150/1875 [00:01<00:22, 77.07it/s, v_num=10, train_loss=0.0678, Acc%=97.00]
Epoch 1: 8%|▊ | 150/1875 [00:01<00:22, 77.06it/s, v_num=10, train_loss=0.0552, Acc%=97.00]
Epoch 1: 8%|▊ | 151/1875 [00:01<00:22, 77.09it/s, v_num=10, train_loss=0.0552, Acc%=97.00]
Epoch 1: 8%|▊ | 151/1875 [00:01<00:22, 77.08it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 8%|▊ | 152/1875 [00:01<00:22, 77.10it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 8%|▊ | 152/1875 [00:01<00:22, 77.09it/s, v_num=10, train_loss=0.0459, Acc%=97.00]
Epoch 1: 8%|▊ | 153/1875 [00:01<00:22, 77.10it/s, v_num=10, train_loss=0.0459, Acc%=97.00]
Epoch 1: 8%|▊ | 153/1875 [00:01<00:22, 77.10it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 8%|▊ | 154/1875 [00:01<00:22, 77.11it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 8%|▊ | 154/1875 [00:01<00:22, 77.11it/s, v_num=10, train_loss=0.187, Acc%=97.00]
Epoch 1: 8%|▊ | 155/1875 [00:02<00:22, 77.12it/s, v_num=10, train_loss=0.187, Acc%=97.00]
Epoch 1: 8%|▊ | 155/1875 [00:02<00:22, 77.12it/s, v_num=10, train_loss=0.0326, Acc%=97.00]
Epoch 1: 8%|▊ | 156/1875 [00:02<00:22, 77.13it/s, v_num=10, train_loss=0.0326, Acc%=97.00]
Epoch 1: 8%|▊ | 156/1875 [00:02<00:22, 77.12it/s, v_num=10, train_loss=0.158, Acc%=97.00]
Epoch 1: 8%|▊ | 157/1875 [00:02<00:22, 77.13it/s, v_num=10, train_loss=0.158, Acc%=97.00]
Epoch 1: 8%|▊ | 157/1875 [00:02<00:22, 77.12it/s, v_num=10, train_loss=0.412, Acc%=97.00]
Epoch 1: 8%|▊ | 158/1875 [00:02<00:22, 77.14it/s, v_num=10, train_loss=0.412, Acc%=97.00]
Epoch 1: 8%|▊ | 158/1875 [00:02<00:22, 77.13it/s, v_num=10, train_loss=0.206, Acc%=97.00]
Epoch 1: 8%|▊ | 159/1875 [00:02<00:22, 77.15it/s, v_num=10, train_loss=0.206, Acc%=97.00]
Epoch 1: 8%|▊ | 159/1875 [00:02<00:22, 77.14it/s, v_num=10, train_loss=0.134, Acc%=97.00]
Epoch 1: 9%|▊ | 160/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.134, Acc%=97.00]
Epoch 1: 9%|▊ | 160/1875 [00:02<00:22, 77.15it/s, v_num=10, train_loss=0.323, Acc%=97.00]
Epoch 1: 9%|▊ | 161/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.323, Acc%=97.00]
Epoch 1: 9%|▊ | 161/1875 [00:02<00:22, 77.15it/s, v_num=10, train_loss=0.200, Acc%=97.00]
Epoch 1: 9%|▊ | 162/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.200, Acc%=97.00]
Epoch 1: 9%|▊ | 162/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.158, Acc%=97.00]
Epoch 1: 9%|▊ | 163/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.158, Acc%=97.00]
Epoch 1: 9%|▊ | 163/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 9%|▊ | 164/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 9%|▊ | 164/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.0563, Acc%=97.00]
Epoch 1: 9%|▉ | 165/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.0563, Acc%=97.00]
Epoch 1: 9%|▉ | 165/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.0444, Acc%=97.00]
Epoch 1: 9%|▉ | 166/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.0444, Acc%=97.00]
Epoch 1: 9%|▉ | 166/1875 [00:02<00:22, 77.15it/s, v_num=10, train_loss=0.237, Acc%=97.00]
Epoch 1: 9%|▉ | 167/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.237, Acc%=97.00]
Epoch 1: 9%|▉ | 167/1875 [00:02<00:22, 77.15it/s, v_num=10, train_loss=0.387, Acc%=97.00]
Epoch 1: 9%|▉ | 168/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.387, Acc%=97.00]
Epoch 1: 9%|▉ | 168/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.0358, Acc%=97.00]
Epoch 1: 9%|▉ | 169/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.0358, Acc%=97.00]
Epoch 1: 9%|▉ | 169/1875 [00:02<00:22, 77.16it/s, v_num=10, train_loss=0.291, Acc%=97.00]
Epoch 1: 9%|▉ | 170/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.291, Acc%=97.00]
Epoch 1: 9%|▉ | 170/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.0498, Acc%=97.00]
Epoch 1: 9%|▉ | 171/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.0498, Acc%=97.00]
Epoch 1: 9%|▉ | 171/1875 [00:02<00:22, 77.17it/s, v_num=10, train_loss=0.154, Acc%=97.00]
Epoch 1: 9%|▉ | 172/1875 [00:02<00:22, 77.19it/s, v_num=10, train_loss=0.154, Acc%=97.00]
Epoch 1: 9%|▉ | 172/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.218, Acc%=97.00]
Epoch 1: 9%|▉ | 173/1875 [00:02<00:22, 77.19it/s, v_num=10, train_loss=0.218, Acc%=97.00]
Epoch 1: 9%|▉ | 173/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.220, Acc%=97.00]
Epoch 1: 9%|▉ | 174/1875 [00:02<00:22, 77.19it/s, v_num=10, train_loss=0.220, Acc%=97.00]
Epoch 1: 9%|▉ | 174/1875 [00:02<00:22, 77.18it/s, v_num=10, train_loss=0.254, Acc%=97.00]
Epoch 1: 9%|▉ | 175/1875 [00:02<00:22, 77.20it/s, v_num=10, train_loss=0.254, Acc%=97.00]
Epoch 1: 9%|▉ | 175/1875 [00:02<00:22, 77.19it/s, v_num=10, train_loss=0.0762, Acc%=97.00]
Epoch 1: 9%|▉ | 176/1875 [00:02<00:22, 77.20it/s, v_num=10, train_loss=0.0762, Acc%=97.00]
Epoch 1: 9%|▉ | 176/1875 [00:02<00:22, 77.19it/s, v_num=10, train_loss=0.0463, Acc%=97.00]
Epoch 1: 9%|▉ | 177/1875 [00:02<00:21, 77.20it/s, v_num=10, train_loss=0.0463, Acc%=97.00]
Epoch 1: 9%|▉ | 177/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.129, Acc%=97.00]
Epoch 1: 9%|▉ | 178/1875 [00:02<00:21, 77.20it/s, v_num=10, train_loss=0.129, Acc%=97.00]
Epoch 1: 9%|▉ | 178/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 10%|▉ | 179/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.0772, Acc%=97.00]
Epoch 1: 10%|▉ | 179/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 10%|▉ | 180/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 10%|▉ | 180/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 10%|▉ | 181/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 10%|▉ | 181/1875 [00:02<00:21, 77.17it/s, v_num=10, train_loss=0.0839, Acc%=97.00]
Epoch 1: 10%|▉ | 182/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.0839, Acc%=97.00]
Epoch 1: 10%|▉ | 182/1875 [00:02<00:21, 77.17it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 10%|▉ | 183/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 10%|▉ | 183/1875 [00:02<00:21, 77.17it/s, v_num=10, train_loss=0.0738, Acc%=97.00]
Epoch 1: 10%|▉ | 184/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.0738, Acc%=97.00]
Epoch 1: 10%|▉ | 184/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 10%|▉ | 185/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 10%|▉ | 185/1875 [00:02<00:21, 77.18it/s, v_num=10, train_loss=0.141, Acc%=97.00]
Epoch 1: 10%|▉ | 186/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.141, Acc%=97.00]
Epoch 1: 10%|▉ | 186/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.0774, Acc%=97.00]
Epoch 1: 10%|▉ | 187/1875 [00:02<00:21, 77.20it/s, v_num=10, train_loss=0.0774, Acc%=97.00]
Epoch 1: 10%|▉ | 187/1875 [00:02<00:21, 77.19it/s, v_num=10, train_loss=0.279, Acc%=97.00]
Epoch 1: 10%|█ | 188/1875 [00:02<00:21, 77.21it/s, v_num=10, train_loss=0.279, Acc%=97.00]
Epoch 1: 10%|█ | 188/1875 [00:02<00:21, 77.20it/s, v_num=10, train_loss=0.374, Acc%=97.00]
Epoch 1: 10%|█ | 189/1875 [00:02<00:21, 77.21it/s, v_num=10, train_loss=0.374, Acc%=97.00]
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Epoch 1: 10%|█ | 190/1875 [00:02<00:21, 77.22it/s, v_num=10, train_loss=0.0809, Acc%=97.00]
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Epoch 1: 10%|█ | 195/1875 [00:02<00:21, 77.21it/s, v_num=10, train_loss=0.241, Acc%=97.00]
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Epoch 1: 11%|█ | 197/1875 [00:02<00:21, 77.21it/s, v_num=10, train_loss=0.307, Acc%=97.00]
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Epoch 1: 11%|█ | 200/1875 [00:02<00:21, 77.14it/s, v_num=10, train_loss=0.167, Acc%=97.00]
Epoch 1: 11%|█ | 201/1875 [00:02<00:21, 77.11it/s, v_num=10, train_loss=0.167, Acc%=97.00]
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Epoch 1: 12%|█▏ | 216/1875 [00:02<00:21, 77.03it/s, v_num=10, train_loss=0.0454, Acc%=97.00]
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Epoch 1: 12%|█▏ | 224/1875 [00:02<00:21, 76.98it/s, v_num=10, train_loss=0.177, Acc%=97.00]
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Epoch 1: 12%|█▏ | 225/1875 [00:02<00:21, 76.98it/s, v_num=10, train_loss=0.318, Acc%=97.00]
Epoch 1: 12%|█▏ | 226/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.318, Acc%=97.00]
Epoch 1: 12%|█▏ | 226/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.0876, Acc%=97.00]
Epoch 1: 12%|█▏ | 227/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.0876, Acc%=97.00]
Epoch 1: 12%|█▏ | 227/1875 [00:02<00:21, 76.96it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 12%|█▏ | 228/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 12%|█▏ | 228/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.0735, Acc%=97.00]
Epoch 1: 12%|█▏ | 229/1875 [00:02<00:21, 76.97it/s, v_num=10, train_loss=0.0735, Acc%=97.00]
Epoch 1: 12%|█▏ | 229/1875 [00:02<00:21, 76.96it/s, v_num=10, train_loss=0.191, Acc%=97.00]
Epoch 1: 12%|█▏ | 230/1875 [00:02<00:21, 76.96it/s, v_num=10, train_loss=0.191, Acc%=97.00]
Epoch 1: 12%|█▏ | 230/1875 [00:02<00:21, 76.96it/s, v_num=10, train_loss=0.133, Acc%=97.00]
Epoch 1: 12%|█▏ | 231/1875 [00:03<00:21, 76.96it/s, v_num=10, train_loss=0.133, Acc%=97.00]
Epoch 1: 12%|█▏ | 231/1875 [00:03<00:21, 76.95it/s, v_num=10, train_loss=0.0982, Acc%=97.00]
Epoch 1: 12%|█▏ | 232/1875 [00:03<00:21, 76.96it/s, v_num=10, train_loss=0.0982, Acc%=97.00]
Epoch 1: 12%|█▏ | 232/1875 [00:03<00:21, 76.95it/s, v_num=10, train_loss=0.0844, Acc%=97.00]
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Epoch 1: 12%|█▏ | 234/1875 [00:03<00:21, 76.97it/s, v_num=10, train_loss=0.0192, Acc%=97.00]
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Epoch 1: 13%|█▎ | 235/1875 [00:03<00:21, 76.97it/s, v_num=10, train_loss=0.0563, Acc%=97.00]
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Epoch 1: 13%|█▎ | 237/1875 [00:03<00:21, 76.99it/s, v_num=10, train_loss=0.0396, Acc%=97.00]
Epoch 1: 13%|█▎ | 237/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 13%|█▎ | 238/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 13%|█▎ | 238/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.0364, Acc%=97.00]
Epoch 1: 13%|█▎ | 239/1875 [00:03<00:21, 76.99it/s, v_num=10, train_loss=0.0364, Acc%=97.00]
Epoch 1: 13%|█▎ | 239/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.0862, Acc%=97.00]
Epoch 1: 13%|█▎ | 240/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.0862, Acc%=97.00]
Epoch 1: 13%|█▎ | 240/1875 [00:03<00:21, 76.98it/s, v_num=10, train_loss=0.366, Acc%=97.00]
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Epoch 1: 13%|█▎ | 244/1875 [00:03<00:21, 76.99it/s, v_num=10, train_loss=0.103, Acc%=97.00]
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Epoch 1: 13%|█▎ | 245/1875 [00:03<00:21, 77.00it/s, v_num=10, train_loss=0.0333, Acc%=97.00]
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Epoch 1: 13%|█▎ | 246/1875 [00:03<00:21, 77.01it/s, v_num=10, train_loss=0.186, Acc%=97.00]
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Epoch 1: 13%|█▎ | 249/1875 [00:03<00:21, 77.03it/s, v_num=10, train_loss=0.306, Acc%=97.00]
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Epoch 1: 14%|█▍ | 265/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.0965, Acc%=97.00]
Epoch 1: 14%|█▍ | 266/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.0965, Acc%=97.00]
Epoch 1: 14%|█▍ | 266/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.0271, Acc%=97.00]
Epoch 1: 14%|█▍ | 267/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.0271, Acc%=97.00]
Epoch 1: 14%|█▍ | 267/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.221, Acc%=97.00]
Epoch 1: 14%|█▍ | 268/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.221, Acc%=97.00]
Epoch 1: 14%|█▍ | 268/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.251, Acc%=97.00]
Epoch 1: 14%|█▍ | 269/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.251, Acc%=97.00]
Epoch 1: 14%|█▍ | 269/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.0955, Acc%=97.00]
Epoch 1: 14%|█▍ | 270/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.0955, Acc%=97.00]
Epoch 1: 14%|█▍ | 270/1875 [00:03<00:20, 77.04it/s, v_num=10, train_loss=0.252, Acc%=97.00]
Epoch 1: 14%|█▍ | 271/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.252, Acc%=97.00]
Epoch 1: 14%|█▍ | 271/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.116, Acc%=97.00]
Epoch 1: 15%|█▍ | 272/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.116, Acc%=97.00]
Epoch 1: 15%|█▍ | 272/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.119, Acc%=97.00]
Epoch 1: 15%|█▍ | 273/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.119, Acc%=97.00]
Epoch 1: 15%|█▍ | 273/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.202, Acc%=97.00]
Epoch 1: 15%|█▍ | 274/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.202, Acc%=97.00]
Epoch 1: 15%|█▍ | 274/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.0439, Acc%=97.00]
Epoch 1: 15%|█▍ | 275/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.0439, Acc%=97.00]
Epoch 1: 15%|█▍ | 275/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 15%|█▍ | 276/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 15%|█▍ | 276/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.0372, Acc%=97.00]
Epoch 1: 15%|█▍ | 277/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.0372, Acc%=97.00]
Epoch 1: 15%|█▍ | 277/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.229, Acc%=97.00]
Epoch 1: 15%|█▍ | 278/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.229, Acc%=97.00]
Epoch 1: 15%|█▍ | 278/1875 [00:03<00:20, 77.05it/s, v_num=10, train_loss=0.227, Acc%=97.00]
Epoch 1: 15%|█▍ | 279/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.227, Acc%=97.00]
Epoch 1: 15%|█▍ | 279/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.203, Acc%=97.00]
Epoch 1: 15%|█▍ | 280/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.203, Acc%=97.00]
Epoch 1: 15%|█▍ | 280/1875 [00:03<00:20, 77.06it/s, v_num=10, train_loss=0.172, Acc%=97.00]
Epoch 1: 15%|█▍ | 281/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.172, Acc%=97.00]
Epoch 1: 15%|█▍ | 281/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 15%|█▌ | 282/1875 [00:03<00:20, 77.08it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 15%|█▌ | 282/1875 [00:03<00:20, 77.07it/s, v_num=10, train_loss=0.0959, Acc%=97.00]
Epoch 1: 15%|█▌ | 283/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.0959, Acc%=97.00]
Epoch 1: 15%|█▌ | 283/1875 [00:03<00:20, 77.08it/s, v_num=10, train_loss=0.122, Acc%=97.00]
Epoch 1: 15%|█▌ | 284/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.122, Acc%=97.00]
Epoch 1: 15%|█▌ | 284/1875 [00:03<00:20, 77.08it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 15%|█▌ | 285/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 15%|█▌ | 285/1875 [00:03<00:20, 77.08it/s, v_num=10, train_loss=0.342, Acc%=97.00]
Epoch 1: 15%|█▌ | 286/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.342, Acc%=97.00]
Epoch 1: 15%|█▌ | 286/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 15%|█▌ | 287/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.211, Acc%=97.00]
Epoch 1: 15%|█▌ | 287/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.345, Acc%=97.00]
Epoch 1: 15%|█▌ | 288/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.345, Acc%=97.00]
Epoch 1: 15%|█▌ | 288/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0719, Acc%=97.00]
Epoch 1: 15%|█▌ | 289/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.0719, Acc%=97.00]
Epoch 1: 15%|█▌ | 289/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 15%|█▌ | 290/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 15%|█▌ | 290/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.449, Acc%=97.00]
Epoch 1: 16%|█▌ | 291/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.449, Acc%=97.00]
Epoch 1: 16%|█▌ | 291/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 16%|█▌ | 292/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 16%|█▌ | 292/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.459, Acc%=97.00]
Epoch 1: 16%|█▌ | 293/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.459, Acc%=97.00]
Epoch 1: 16%|█▌ | 293/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 16%|█▌ | 294/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.224, Acc%=97.00]
Epoch 1: 16%|█▌ | 294/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.0695, Acc%=97.00]
Epoch 1: 16%|█▌ | 295/1875 [00:03<00:20, 77.14it/s, v_num=10, train_loss=0.0695, Acc%=97.00]
Epoch 1: 16%|█▌ | 295/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.116, Acc%=97.00]
Epoch 1: 16%|█▌ | 296/1875 [00:03<00:20, 77.14it/s, v_num=10, train_loss=0.116, Acc%=97.00]
Epoch 1: 16%|█▌ | 296/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.0476, Acc%=97.00]
Epoch 1: 16%|█▌ | 297/1875 [00:03<00:20, 77.14it/s, v_num=10, train_loss=0.0476, Acc%=97.00]
Epoch 1: 16%|█▌ | 297/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.186, Acc%=97.00]
Epoch 1: 16%|█▌ | 298/1875 [00:03<00:20, 77.14it/s, v_num=10, train_loss=0.186, Acc%=97.00]
Epoch 1: 16%|█▌ | 298/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 16%|█▌ | 299/1875 [00:03<00:20, 77.13it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 16%|█▌ | 299/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.205, Acc%=97.00]
Epoch 1: 16%|█▌ | 300/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.205, Acc%=97.00]
Epoch 1: 16%|█▌ | 300/1875 [00:03<00:20, 77.12it/s, v_num=10, train_loss=0.0368, Acc%=97.00]
Epoch 1: 16%|█▌ | 301/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0368, Acc%=97.00]
Epoch 1: 16%|█▌ | 301/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0155, Acc%=97.00]
Epoch 1: 16%|█▌ | 302/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0155, Acc%=97.00]
Epoch 1: 16%|█▌ | 302/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 16%|█▌ | 303/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 16%|█▌ | 303/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.246, Acc%=97.00]
Epoch 1: 16%|█▌ | 304/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.246, Acc%=97.00]
Epoch 1: 16%|█▌ | 304/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0329, Acc%=97.00]
Epoch 1: 16%|█▋ | 305/1875 [00:03<00:20, 77.11it/s, v_num=10, train_loss=0.0329, Acc%=97.00]
Epoch 1: 16%|█▋ | 305/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 16%|█▋ | 306/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.104, Acc%=97.00]
Epoch 1: 16%|█▋ | 306/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0816, Acc%=97.00]
Epoch 1: 16%|█▋ | 307/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.0816, Acc%=97.00]
Epoch 1: 16%|█▋ | 307/1875 [00:03<00:20, 77.09it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 16%|█▋ | 308/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 16%|█▋ | 308/1875 [00:03<00:20, 77.10it/s, v_num=10, train_loss=0.277, Acc%=97.00]
Epoch 1: 16%|█▋ | 309/1875 [00:04<00:20, 77.10it/s, v_num=10, train_loss=0.277, Acc%=97.00]
Epoch 1: 16%|█▋ | 309/1875 [00:04<00:20, 77.10it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 17%|█▋ | 310/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.201, Acc%=97.00]
Epoch 1: 17%|█▋ | 310/1875 [00:04<00:20, 77.10it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 17%|█▋ | 311/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 17%|█▋ | 311/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.083, Acc%=97.00]
Epoch 1: 17%|█▋ | 312/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.083, Acc%=97.00]
Epoch 1: 17%|█▋ | 312/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 17%|█▋ | 313/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 17%|█▋ | 313/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 17%|█▋ | 314/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.153, Acc%=97.00]
Epoch 1: 17%|█▋ | 314/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.0812, Acc%=97.00]
Epoch 1: 17%|█▋ | 315/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.0812, Acc%=97.00]
Epoch 1: 17%|█▋ | 315/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.195, Acc%=97.00]
Epoch 1: 17%|█▋ | 316/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.195, Acc%=97.00]
Epoch 1: 17%|█▋ | 316/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.0883, Acc%=97.00]
Epoch 1: 17%|█▋ | 317/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.0883, Acc%=97.00]
Epoch 1: 17%|█▋ | 317/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.186, Acc%=97.00]
Epoch 1: 17%|█▋ | 318/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.186, Acc%=97.00]
Epoch 1: 17%|█▋ | 318/1875 [00:04<00:20, 77.11it/s, v_num=10, train_loss=0.094, Acc%=97.00]
Epoch 1: 17%|█▋ | 319/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.094, Acc%=97.00]
Epoch 1: 17%|█▋ | 319/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 17%|█▋ | 320/1875 [00:04<00:20, 77.13it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 17%|█▋ | 320/1875 [00:04<00:20, 77.12it/s, v_num=10, train_loss=0.180, Acc%=97.00]
Epoch 1: 17%|█▋ | 321/1875 [00:04<00:20, 77.13it/s, v_num=10, train_loss=0.180, Acc%=97.00]
Epoch 1: 17%|█▋ | 321/1875 [00:04<00:20, 77.13it/s, v_num=10, train_loss=0.468, Acc%=97.00]
Epoch 1: 17%|█▋ | 322/1875 [00:04<00:20, 77.14it/s, v_num=10, train_loss=0.468, Acc%=97.00]
Epoch 1: 17%|█▋ | 322/1875 [00:04<00:20, 77.14it/s, v_num=10, train_loss=0.570, Acc%=97.00]
Epoch 1: 17%|█▋ | 323/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.570, Acc%=97.00]
Epoch 1: 17%|█▋ | 323/1875 [00:04<00:20, 77.14it/s, v_num=10, train_loss=0.0462, Acc%=97.00]
Epoch 1: 17%|█▋ | 324/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.0462, Acc%=97.00]
Epoch 1: 17%|█▋ | 324/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.362, Acc%=97.00]
Epoch 1: 17%|█▋ | 325/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.362, Acc%=97.00]
Epoch 1: 17%|█▋ | 325/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.0261, Acc%=97.00]
Epoch 1: 17%|█▋ | 326/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.0261, Acc%=97.00]
Epoch 1: 17%|█▋ | 326/1875 [00:04<00:20, 77.15it/s, v_num=10, train_loss=0.152, Acc%=97.00]
Epoch 1: 17%|█▋ | 327/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.152, Acc%=97.00]
Epoch 1: 17%|█▋ | 327/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.112, Acc%=97.00]
Epoch 1: 17%|█▋ | 328/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.112, Acc%=97.00]
Epoch 1: 17%|█▋ | 328/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.214, Acc%=97.00]
Epoch 1: 18%|█▊ | 329/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.214, Acc%=97.00]
Epoch 1: 18%|█▊ | 329/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.146, Acc%=97.00]
Epoch 1: 18%|█▊ | 330/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.146, Acc%=97.00]
Epoch 1: 18%|█▊ | 330/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.216, Acc%=97.00]
Epoch 1: 18%|█▊ | 331/1875 [00:04<00:20, 77.17it/s, v_num=10, train_loss=0.216, Acc%=97.00]
Epoch 1: 18%|█▊ | 331/1875 [00:04<00:20, 77.16it/s, v_num=10, train_loss=0.192, Acc%=97.00]
Epoch 1: 18%|█▊ | 332/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.192, Acc%=97.00]
Epoch 1: 18%|█▊ | 332/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.065, Acc%=97.00]
Epoch 1: 18%|█▊ | 333/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.065, Acc%=97.00]
Epoch 1: 18%|█▊ | 333/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.236, Acc%=97.00]
Epoch 1: 18%|█▊ | 334/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.236, Acc%=97.00]
Epoch 1: 18%|█▊ | 334/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.0707, Acc%=97.00]
Epoch 1: 18%|█▊ | 335/1875 [00:04<00:19, 77.18it/s, v_num=10, train_loss=0.0707, Acc%=97.00]
Epoch 1: 18%|█▊ | 335/1875 [00:04<00:19, 77.17it/s, v_num=10, train_loss=0.370, Acc%=97.00]
Epoch 1: 18%|█▊ | 336/1875 [00:04<00:19, 77.18it/s, v_num=10, train_loss=0.370, Acc%=97.00]
Epoch 1: 18%|█▊ | 336/1875 [00:04<00:19, 77.18it/s, v_num=10, train_loss=0.109, Acc%=97.00]
Epoch 1: 18%|█▊ | 337/1875 [00:04<00:19, 77.19it/s, v_num=10, train_loss=0.109, Acc%=97.00]
Epoch 1: 18%|█▊ | 337/1875 [00:04<00:19, 77.18it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 18%|█▊ | 338/1875 [00:04<00:19, 77.19it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 18%|█▊ | 338/1875 [00:04<00:19, 77.19it/s, v_num=10, train_loss=0.0784, Acc%=97.00]
Epoch 1: 18%|█▊ | 339/1875 [00:04<00:19, 77.20it/s, v_num=10, train_loss=0.0784, Acc%=97.00]
Epoch 1: 18%|█▊ | 339/1875 [00:04<00:19, 77.20it/s, v_num=10, train_loss=0.0643, Acc%=97.00]
Epoch 1: 18%|█▊ | 340/1875 [00:04<00:19, 77.20it/s, v_num=10, train_loss=0.0643, Acc%=97.00]
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Epoch 1: 18%|█▊ | 341/1875 [00:04<00:19, 77.21it/s, v_num=10, train_loss=0.472, Acc%=97.00]
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Epoch 1: 54%|█████▍ | 1010/1875 [00:13<00:11, 77.54it/s, v_num=10, train_loss=0.0495, Acc%=97.00]
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Epoch 1: 54%|█████▍ | 1013/1875 [00:13<00:11, 77.53it/s, v_num=10, train_loss=0.139, Acc%=97.00]
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Epoch 1: 55%|█████▍ | 1024/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.189, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1043/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.040, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1046/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.0411, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1051/1875 [00:13<00:10, 77.53it/s, v_num=10, train_loss=0.124, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1052/1875 [00:13<00:10, 77.53it/s, v_num=10, train_loss=0.378, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1053/1875 [00:13<00:10, 77.53it/s, v_num=10, train_loss=0.334, Acc%=97.00]
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Epoch 1: 56%|█████▌ | 1054/1875 [00:13<00:10, 77.53it/s, v_num=10, train_loss=0.105, Acc%=97.00]
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Epoch 1: 56%|█████▋ | 1055/1875 [00:13<00:10, 77.53it/s, v_num=10, train_loss=0.0991, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1079/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.154, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1079/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.228, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1080/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.228, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1080/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.178, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1081/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.178, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1081/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.189, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1082/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.183, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1083/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.0447, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1084/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.094, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1085/1875 [00:13<00:10, 77.52it/s, v_num=10, train_loss=0.0726, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1086/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.194, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1087/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.194, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1087/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.190, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1088/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1089/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.123, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1089/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.0812, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1090/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.0812, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1090/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1091/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 58%|█████▊ | 1091/1875 [00:14<00:10, 77.53it/s, v_num=10, train_loss=0.208, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1092/1875 [00:14<00:10, 77.51it/s, v_num=10, train_loss=0.126, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1093/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.071, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1094/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.116, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1095/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.0699, Acc%=97.00]
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Epoch 1: 58%|█████▊ | 1096/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.00844, Acc%=97.00]
Epoch 1: 59%|█████▊ | 1097/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.00844, Acc%=97.00]
Epoch 1: 59%|█████▊ | 1097/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.209, Acc%=97.00]
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Epoch 1: 59%|█████▊ | 1098/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.310, Acc%=97.00]
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Epoch 1: 59%|█████▊ | 1099/1875 [00:14<00:10, 77.50it/s, v_num=10, train_loss=0.213, Acc%=97.00]
Epoch 1: 59%|█████▊ | 1100/1875 [00:14<00:09, 77.50it/s, v_num=10, train_loss=0.213, Acc%=97.00]
Epoch 1: 59%|█████▊ | 1100/1875 [00:14<00:09, 77.50it/s, v_num=10, train_loss=0.133, Acc%=97.00]
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Epoch 1: 59%|█████▊ | 1101/1875 [00:14<00:09, 77.50it/s, v_num=10, train_loss=0.137, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1102/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.137, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1102/1875 [00:14<00:09, 77.50it/s, v_num=10, train_loss=0.137, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1103/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.464, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1104/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.464, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1104/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.278, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1105/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.124, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1106/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.124, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1106/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0722, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1107/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.172, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1108/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0262, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1109/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0497, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1110/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.174, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1111/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.174, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1111/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.146, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1112/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1113/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0682, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1113/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.102, Acc%=97.00]
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Epoch 1: 59%|█████▉ | 1114/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.317, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1115/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.317, Acc%=97.00]
Epoch 1: 59%|█████▉ | 1115/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.237, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1116/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.237, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1116/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.132, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1117/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.132, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1117/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.095, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1118/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.095, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1118/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1119/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1119/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.199, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1120/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.199, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1120/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0625, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1121/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0625, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1121/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0262, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1122/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0262, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1122/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.062, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1123/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.062, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1123/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1124/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 60%|█████▉ | 1124/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.243, Acc%=97.00]
Epoch 1: 60%|██████ | 1125/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.243, Acc%=97.00]
Epoch 1: 60%|██████ | 1125/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.245, Acc%=97.00]
Epoch 1: 60%|██████ | 1126/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.245, Acc%=97.00]
Epoch 1: 60%|██████ | 1126/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.0588, Acc%=97.00]
Epoch 1: 60%|██████ | 1127/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0588, Acc%=97.00]
Epoch 1: 60%|██████ | 1127/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.118, Acc%=97.00]
Epoch 1: 60%|██████ | 1128/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.118, Acc%=97.00]
Epoch 1: 60%|██████ | 1128/1875 [00:14<00:09, 77.51it/s, v_num=10, train_loss=0.156, Acc%=97.00]
Epoch 1: 60%|██████ | 1129/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.156, Acc%=97.00]
Epoch 1: 60%|██████ | 1129/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0574, Acc%=97.00]
Epoch 1: 60%|██████ | 1130/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0574, Acc%=97.00]
Epoch 1: 60%|██████ | 1130/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.299, Acc%=97.00]
Epoch 1: 60%|██████ | 1131/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.299, Acc%=97.00]
Epoch 1: 60%|██████ | 1131/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.143, Acc%=97.00]
Epoch 1: 60%|██████ | 1132/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.143, Acc%=97.00]
Epoch 1: 60%|██████ | 1132/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.254, Acc%=97.00]
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Epoch 1: 60%|██████ | 1133/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.152, Acc%=97.00]
Epoch 1: 60%|██████ | 1134/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.152, Acc%=97.00]
Epoch 1: 60%|██████ | 1134/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 61%|██████ | 1135/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.145, Acc%=97.00]
Epoch 1: 61%|██████ | 1135/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0437, Acc%=97.00]
Epoch 1: 61%|██████ | 1136/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0437, Acc%=97.00]
Epoch 1: 61%|██████ | 1136/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0461, Acc%=97.00]
Epoch 1: 61%|██████ | 1137/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0461, Acc%=97.00]
Epoch 1: 61%|██████ | 1137/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.434, Acc%=97.00]
Epoch 1: 61%|██████ | 1138/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.434, Acc%=97.00]
Epoch 1: 61%|██████ | 1138/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0806, Acc%=97.00]
Epoch 1: 61%|██████ | 1139/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0806, Acc%=97.00]
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Epoch 1: 61%|██████ | 1140/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.098, Acc%=97.00]
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Epoch 1: 61%|██████ | 1141/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.217, Acc%=97.00]
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Epoch 1: 61%|██████ | 1142/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0583, Acc%=97.00]
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Epoch 1: 61%|██████ | 1146/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0229, Acc%=97.00]
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Epoch 1: 61%|██████ | 1147/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0753, Acc%=97.00]
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Epoch 1: 61%|██████▏ | 1149/1875 [00:14<00:09, 77.52it/s, v_num=10, train_loss=0.0283, Acc%=97.00]
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Epoch 1: 61%|██████▏ | 1150/1875 [00:14<00:09, 77.53it/s, v_num=10, train_loss=0.114, Acc%=97.00]
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Epoch 1: 61%|██████▏ | 1151/1875 [00:14<00:09, 77.53it/s, v_num=10, train_loss=0.169, Acc%=97.00]
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Epoch 1: 62%|██████▏ | 1157/1875 [00:14<00:09, 77.53it/s, v_num=10, train_loss=0.0997, Acc%=97.00]
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Epoch 1: 62%|██████▏ | 1160/1875 [00:14<00:09, 77.53it/s, v_num=10, train_loss=0.204, Acc%=97.00]
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Epoch 1: 62%|██████▏ | 1161/1875 [00:14<00:09, 77.53it/s, v_num=10, train_loss=0.108, Acc%=97.00]
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Epoch 1: 63%|██████▎ | 1186/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.128, Acc%=97.00]
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Epoch 1: 63%|██████▎ | 1187/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.0624, Acc%=97.00]
Epoch 1: 63%|██████▎ | 1188/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.0624, Acc%=97.00]
Epoch 1: 63%|██████▎ | 1188/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.193, Acc%=97.00]
Epoch 1: 63%|██████▎ | 1189/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.193, Acc%=97.00]
Epoch 1: 63%|██████▎ | 1189/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.116, Acc%=97.00]
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Epoch 1: 63%|██████▎ | 1190/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.109, Acc%=97.00]
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Epoch 1: 64%|██████▎ | 1193/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.279, Acc%=97.00]
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Epoch 1: 64%|██████▍ | 1197/1875 [00:15<00:08, 77.52it/s, v_num=10, train_loss=0.0498, Acc%=97.00]
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Epoch 1: 64%|██████▍ | 1200/1875 [00:15<00:08, 77.53it/s, v_num=10, train_loss=0.0191, Acc%=97.00]
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Epoch 1: 67%|██████▋ | 1259/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.031, Acc%=97.00]
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Epoch 1: 67%|██████▋ | 1260/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.0316, Acc%=97.00]
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Epoch 1: 67%|██████▋ | 1261/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.242, Acc%=97.00]
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Epoch 1: 68%|██████▊ | 1268/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.369, Acc%=97.00]
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Epoch 1: 68%|██████▊ | 1269/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.232, Acc%=97.00]
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Epoch 1: 68%|██████▊ | 1270/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.343, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1295/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.117, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1296/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 69%|██████▉ | 1297/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.114, Acc%=97.00]
Epoch 1: 69%|██████▉ | 1297/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.0323, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1298/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.300, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1299/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.0818, Acc%=97.00]
Epoch 1: 69%|██████▉ | 1300/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.0818, Acc%=97.00]
Epoch 1: 69%|██████▉ | 1300/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.163, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1302/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.270, Acc%=97.00]
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Epoch 1: 69%|██████▉ | 1303/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.163, Acc%=97.00]
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Epoch 1: 70%|██████▉ | 1304/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.199, Acc%=97.00]
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Epoch 1: 70%|██████▉ | 1305/1875 [00:16<00:07, 77.56it/s, v_num=10, train_loss=0.146, Acc%=97.00]
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Epoch 1: 70%|██████▉ | 1307/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.0396, Acc%=97.00]
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Epoch 1: 70%|██████▉ | 1308/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.394, Acc%=97.00]
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Epoch 1: 70%|██████▉ | 1309/1875 [00:16<00:07, 77.55it/s, v_num=10, train_loss=0.108, Acc%=97.00]
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Epoch 1: 70%|███████ | 1320/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.0362, Acc%=97.00]
Epoch 1: 70%|███████ | 1321/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.0362, Acc%=97.00]
Epoch 1: 70%|███████ | 1321/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.048, Acc%=97.00]
Epoch 1: 71%|███████ | 1322/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.048, Acc%=97.00]
Epoch 1: 71%|███████ | 1322/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.0583, Acc%=97.00]
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Epoch 1: 71%|███████ | 1323/1875 [00:17<00:07, 77.55it/s, v_num=10, train_loss=0.101, Acc%=97.00]
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Epoch 1: 71%|███████ | 1326/1875 [00:17<00:07, 77.54it/s, v_num=10, train_loss=0.113, Acc%=97.00]
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Epoch 1: 71%|███████ | 1327/1875 [00:17<00:07, 77.54it/s, v_num=10, train_loss=0.0388, Acc%=97.00]
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Epoch 1: 71%|███████ | 1328/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.231, Acc%=97.00]
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Epoch 1: 71%|███████ | 1329/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.0214, Acc%=97.00]
Epoch 1: 71%|███████ | 1330/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.0214, Acc%=97.00]
Epoch 1: 71%|███████ | 1330/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 71%|███████ | 1331/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.256, Acc%=97.00]
Epoch 1: 71%|███████ | 1331/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.148, Acc%=97.00]
Epoch 1: 71%|███████ | 1332/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.148, Acc%=97.00]
Epoch 1: 71%|███████ | 1332/1875 [00:17<00:07, 77.53it/s, v_num=10, train_loss=0.0657, Acc%=97.00]
Epoch 1: 71%|███████ | 1333/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0657, Acc%=97.00]
Epoch 1: 71%|███████ | 1333/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0744, Acc%=97.00]
Epoch 1: 71%|███████ | 1334/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0744, Acc%=97.00]
Epoch 1: 71%|███████ | 1334/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0231, Acc%=97.00]
Epoch 1: 71%|███████ | 1335/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0231, Acc%=97.00]
Epoch 1: 71%|███████ | 1335/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.069, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1336/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.069, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1336/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.117, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1337/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.117, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1337/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1338/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.115, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1338/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0587, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1339/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0587, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1339/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.014, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1340/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.014, Acc%=97.00]
Epoch 1: 71%|███████▏ | 1340/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0309, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1341/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0309, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1341/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0904, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1342/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0904, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1342/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0926, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1343/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0926, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1343/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0972, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1344/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.370, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1345/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0172, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1347/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.304, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1347/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.220, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1348/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.220, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1348/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.353, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1349/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.353, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1349/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.520, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1350/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.520, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1350/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0261, Acc%=97.00]
Epoch 1: 72%|███████▏ | 1351/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0261, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1352/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0748, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1353/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.260, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1354/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.227, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1355/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.156, Acc%=97.00]
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Epoch 1: 72%|███████▏ | 1357/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.118, Acc%=97.00]
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Epoch 1: 73%|███████▎ | 1361/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.249, Acc%=97.00]
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Epoch 1: 73%|███████▎ | 1362/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.214, Acc%=97.00]
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Epoch 1: 73%|███████▎ | 1363/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.164, Acc%=97.00]
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Epoch 1: 73%|███████▎ | 1365/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1366/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.147, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1366/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.312, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1367/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.312, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1367/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.137, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1368/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.137, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1368/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0957, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1369/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0957, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1369/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.117, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1370/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.117, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1370/1875 [00:17<00:06, 77.53it/s, v_num=10, train_loss=0.0365, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1371/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0365, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1371/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.216, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1372/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.216, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1372/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.102, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1373/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.102, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1373/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1374/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1374/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0738, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1375/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0738, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1375/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.00788, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1376/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.00788, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1376/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0268, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1377/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0268, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1377/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0785, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1378/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0785, Acc%=97.00]
Epoch 1: 73%|███████▎ | 1378/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0839, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1379/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0839, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1379/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0177, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1380/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0177, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1380/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0252, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1381/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0252, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1381/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.184, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1382/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.184, Acc%=97.00]
Epoch 1: 74%|███████▎ | 1382/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0798, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1383/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0798, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1383/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0547, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1384/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0547, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1384/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.147, Acc%=97.00]
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Epoch 1: 74%|███████▍ | 1385/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.124, Acc%=97.00]
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Epoch 1: 74%|███████▍ | 1386/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0633, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1387/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0633, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1387/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0648, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1388/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0648, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1388/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.131, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1389/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.131, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1389/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0817, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1390/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0817, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1390/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.193, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1391/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.193, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1391/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0387, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1392/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0387, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1392/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1393/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1393/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.184, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1394/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.184, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1394/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.0578, Acc%=97.00]
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Epoch 1: 74%|███████▍ | 1395/1875 [00:17<00:06, 77.52it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1396/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.189, Acc%=97.00]
Epoch 1: 74%|███████▍ | 1396/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.0307, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1397/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.0307, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1397/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.124, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1398/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.124, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1398/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.335, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1399/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.335, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1399/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.275, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1400/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.275, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1400/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.403, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1401/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.403, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1401/1875 [00:18<00:06, 77.52it/s, v_num=10, train_loss=0.0679, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1402/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.0679, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1402/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.0249, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1403/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.0249, Acc%=97.00]
Epoch 1: 75%|███████▍ | 1403/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.0467, Acc%=97.00]
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Epoch 1: 75%|███████▍ | 1404/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.466, Acc%=97.00]
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Epoch 1: 75%|███████▍ | 1405/1875 [00:18<00:06, 77.51it/s, v_num=10, train_loss=0.122, Acc%=97.00]
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Epoch 1: 75%|███████▍ | 1406/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.121, Acc%=97.00]
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Epoch 1: 75%|███████▌ | 1407/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.0753, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1408/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.0753, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1408/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.454, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1409/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.454, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1409/1875 [00:18<00:06, 77.50it/s, v_num=10, train_loss=0.202, Acc%=97.00]
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Epoch 1: 75%|███████▌ | 1410/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.228, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1411/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.228, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1411/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.159, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1412/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.159, Acc%=97.00]
Epoch 1: 75%|███████▌ | 1412/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.263, Acc%=97.00]
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Epoch 1: 75%|███████▌ | 1413/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.350, Acc%=97.00]
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Epoch 1: 75%|███████▌ | 1415/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.218, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1416/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0783, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1417/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0453, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1418/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.156, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1419/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.168, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1420/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0499, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1421/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.243, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1422/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.125, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1426/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0503, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1427/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.104, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1428/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.305, Acc%=97.00]
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Epoch 1: 76%|███████▌ | 1429/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.204, Acc%=97.00]
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Epoch 1: 76%|███████▋ | 1430/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0973, Acc%=97.00]
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Epoch 1: 76%|███████▋ | 1431/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.137, Acc%=97.00]
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Epoch 1: 76%|███████▋ | 1432/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.086, Acc%=97.00]
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Epoch 1: 76%|███████▋ | 1433/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0267, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1435/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.167, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1436/1875 [00:18<00:05, 77.51it/s, v_num=10, train_loss=0.0722, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1437/1875 [00:18<00:05, 77.51it/s, v_num=10, train_loss=0.0722, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1437/1875 [00:18<00:05, 77.51it/s, v_num=10, train_loss=0.158, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1438/1875 [00:18<00:05, 77.51it/s, v_num=10, train_loss=0.150, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1439/1875 [00:18<00:05, 77.51it/s, v_num=10, train_loss=0.0639, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1440/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0721, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1441/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0359, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1442/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0963, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1443/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.00834, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1444/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.150, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1445/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0547, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1446/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.151, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1447/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0529, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1448/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.0529, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1448/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.113, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1449/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.054, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1450/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.118, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1451/1875 [00:18<00:05, 77.50it/s, v_num=10, train_loss=0.118, Acc%=97.00]
Epoch 1: 77%|███████▋ | 1451/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.387, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1452/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.132, Acc%=97.00]
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Epoch 1: 77%|███████▋ | 1453/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.113, Acc%=97.00]
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Epoch 1: 78%|███████▊ | 1454/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.129, Acc%=97.00]
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Epoch 1: 78%|███████▊ | 1455/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.370, Acc%=97.00]
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Epoch 1: 78%|███████▊ | 1456/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.126, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1457/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.126, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1457/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0568, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1458/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0568, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1458/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0346, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1459/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0346, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1459/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0758, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1460/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0758, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1460/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.239, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1461/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.239, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1461/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.174, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1462/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.174, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1462/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.294, Acc%=97.00]
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Epoch 1: 78%|███████▊ | 1463/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0927, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1464/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0927, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1464/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.232, Acc%=97.00]
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Epoch 1: 78%|███████▊ | 1465/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.112, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1466/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.112, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1466/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.136, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1467/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.136, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1467/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1468/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1468/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0515, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1469/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0515, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1469/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.372, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1470/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.372, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1470/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.170, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1471/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.170, Acc%=97.00]
Epoch 1: 78%|███████▊ | 1471/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0153, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1472/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.0153, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1472/1875 [00:18<00:05, 77.49it/s, v_num=10, train_loss=0.227, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1473/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.227, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1473/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0274, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1474/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0274, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1474/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0692, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1475/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0692, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1475/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.244, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1476/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.244, Acc%=97.00]
Epoch 1: 79%|███████▊ | 1476/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0641, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1477/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0641, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1477/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0183, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1478/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0183, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1478/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0398, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1479/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0398, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1479/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1480/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.121, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1480/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0287, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1481/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0287, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1481/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.0794, Acc%=97.00]
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Epoch 1: 79%|███████▉ | 1482/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.130, Acc%=97.00]
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Epoch 1: 79%|███████▉ | 1483/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.239, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1484/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.239, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1484/1875 [00:19<00:05, 77.49it/s, v_num=10, train_loss=0.214, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1485/1875 [00:19<00:05, 77.48it/s, v_num=10, train_loss=0.214, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1485/1875 [00:19<00:05, 77.48it/s, v_num=10, train_loss=0.0684, Acc%=97.00]
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Epoch 1: 79%|███████▉ | 1486/1875 [00:19<00:05, 77.47it/s, v_num=10, train_loss=0.192, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1487/1875 [00:19<00:05, 77.47it/s, v_num=10, train_loss=0.192, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1487/1875 [00:19<00:05, 77.47it/s, v_num=10, train_loss=0.182, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1488/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.182, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1488/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.0693, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1489/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.0693, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1489/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.226, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1490/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.226, Acc%=97.00]
Epoch 1: 79%|███████▉ | 1490/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.213, Acc%=97.00]
Epoch 1: 80%|███████▉ | 1491/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.213, Acc%=97.00]
Epoch 1: 80%|███████▉ | 1491/1875 [00:19<00:04, 77.47it/s, v_num=10, train_loss=0.0392, Acc%=97.00]
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Epoch 1: 80%|███████▉ | 1494/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.139, Acc%=97.00]
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Epoch 1: 80%|███████▉ | 1495/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.0294, Acc%=97.00]
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Epoch 1: 80%|███████▉ | 1499/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 80%|████████ | 1500/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 80%|████████ | 1500/1875 [00:19<00:04, 77.48it/s, v_num=10, train_loss=0.273, Acc%=97.00]
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Epoch 1: 84%|████████▍ | 1577/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.112, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1577/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.159, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1578/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.159, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1578/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.0936, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1579/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.0936, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1579/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1580/1875 [00:20<00:03, 77.53it/s, v_num=10, train_loss=0.107, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1580/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.145, Acc%=97.00]
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Epoch 1: 84%|████████▍ | 1581/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.126, Acc%=97.00]
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Epoch 1: 84%|████████▍ | 1582/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.117, Acc%=97.00]
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Epoch 1: 84%|████████▍ | 1583/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.0202, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1584/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.0202, Acc%=97.00]
Epoch 1: 84%|████████▍ | 1584/1875 [00:20<00:03, 77.52it/s, v_num=10, train_loss=0.0831, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1585/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0831, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1585/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.212, Acc%=97.00]
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Epoch 1: 85%|████████▍ | 1586/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.268, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1587/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.268, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1587/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.196, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1588/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.196, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1588/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.101, Acc%=97.00]
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Epoch 1: 85%|████████▍ | 1589/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.106, Acc%=97.00]
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Epoch 1: 85%|████████▍ | 1590/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.149, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1591/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.149, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1591/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.0582, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1592/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0582, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1592/1875 [00:20<00:03, 77.49it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1593/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 85%|████████▍ | 1593/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.429, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1594/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.429, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1594/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
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Epoch 1: 85%|████████▌ | 1595/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0905, Acc%=97.00]
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Epoch 1: 85%|████████▌ | 1598/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0245, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1598/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.182, Acc%=97.00]
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Epoch 1: 85%|████████▌ | 1599/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.140, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1600/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.140, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1600/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.204, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1601/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.204, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1601/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0537, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1602/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0537, Acc%=97.00]
Epoch 1: 85%|████████▌ | 1602/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.123, Acc%=97.00]
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Epoch 1: 85%|████████▌ | 1603/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0447, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1604/1875 [00:20<00:03, 77.50it/s, v_num=10, train_loss=0.0858, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1606/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.154, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1607/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0514, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1608/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.232, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1609/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.232, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1609/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0527, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1610/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0527, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1610/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0645, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1611/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1612/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1612/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.182, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1613/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.182, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1613/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.00947, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1614/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.00947, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1614/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1615/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.138, Acc%=97.00]
Epoch 1: 86%|████████▌ | 1615/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.297, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1616/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0721, Acc%=97.00]
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Epoch 1: 86%|████████▌ | 1617/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.206, Acc%=97.00]
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Epoch 1: 86%|████████▋ | 1618/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.157, Acc%=97.00]
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Epoch 1: 86%|████████▋ | 1619/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.293, Acc%=97.00]
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Epoch 1: 86%|████████▋ | 1620/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.446, Acc%=97.00]
Epoch 1: 86%|████████▋ | 1621/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.446, Acc%=97.00]
Epoch 1: 86%|████████▋ | 1621/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0339, Acc%=97.00]
Epoch 1: 87%|████████▋ | 1622/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0339, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1623/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.126, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1624/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.253, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1625/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.161, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1626/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.0257, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1627/1875 [00:20<00:03, 77.51it/s, v_num=10, train_loss=0.119, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1628/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.0597, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1629/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.123, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1630/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.156, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1631/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.0965, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1633/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.288, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1634/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.0995, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1635/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.151, Acc%=97.00]
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Epoch 1: 87%|████████▋ | 1638/1875 [00:21<00:03, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1641/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.0789, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1641/1875 [00:21<00:03, 77.50it/s, v_num=10, train_loss=0.322, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1642/1875 [00:21<00:03, 77.51it/s, v_num=10, train_loss=0.0703, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1643/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.311, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1644/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0192, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1645/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0305, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1646/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0305, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1646/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.085, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1647/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.085, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1647/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0447, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1648/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0447, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1648/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.062, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1649/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.062, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1649/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0724, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1650/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0724, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1650/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.257, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1651/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.257, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1651/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1652/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.100, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1652/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0397, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1653/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0397, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1653/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.129, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1654/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.129, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1654/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0575, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1655/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0575, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1655/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.117, Acc%=97.00]
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Epoch 1: 88%|████████▊ | 1656/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0399, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1657/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0399, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1657/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1658/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.176, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1658/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0626, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1659/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0626, Acc%=97.00]
Epoch 1: 88%|████████▊ | 1659/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0799, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1660/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0799, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1660/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0748, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1661/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0748, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1661/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0644, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1662/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0644, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1662/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.129, Acc%=97.00]
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Epoch 1: 89%|████████▊ | 1663/1875 [00:21<00:02, 77.48it/s, v_num=10, train_loss=0.0477, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1664/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0477, Acc%=97.00]
Epoch 1: 89%|████████▊ | 1664/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.394, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1665/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.394, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1665/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.330, Acc%=97.00]
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Epoch 1: 89%|████████▉ | 1666/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.207, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1667/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.207, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1667/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.612, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1668/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.612, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1668/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.511, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1669/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.511, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1669/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.127, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1670/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.127, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1670/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1671/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1671/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0265, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1672/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0265, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1672/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0126, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1673/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0126, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1673/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0847, Acc%=97.00]
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Epoch 1: 89%|████████▉ | 1674/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1675/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.105, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1675/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.219, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1676/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.219, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1676/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0679, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1677/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0679, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1677/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0623, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1678/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0623, Acc%=97.00]
Epoch 1: 89%|████████▉ | 1678/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.0508, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1679/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0508, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1679/1875 [00:21<00:02, 77.49it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1680/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.111, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1680/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.249, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1681/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.249, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1681/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0922, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1682/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0922, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1682/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0181, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1683/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0181, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1683/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0755, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1684/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0755, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1684/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1685/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.160, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1685/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1686/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1686/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.235, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1687/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.235, Acc%=97.00]
Epoch 1: 90%|████████▉ | 1687/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 90%|█████████ | 1688/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.108, Acc%=97.00]
Epoch 1: 90%|█████████ | 1688/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.328, Acc%=97.00]
Epoch 1: 90%|█████████ | 1689/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.328, Acc%=97.00]
Epoch 1: 90%|█████████ | 1689/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
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Epoch 1: 90%|█████████ | 1690/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
Epoch 1: 90%|█████████ | 1691/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.155, Acc%=97.00]
Epoch 1: 90%|█████████ | 1691/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.545, Acc%=97.00]
Epoch 1: 90%|█████████ | 1692/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.545, Acc%=97.00]
Epoch 1: 90%|█████████ | 1692/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.453, Acc%=97.00]
Epoch 1: 90%|█████████ | 1693/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.453, Acc%=97.00]
Epoch 1: 90%|█████████ | 1693/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.0977, Acc%=97.00]
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Epoch 1: 90%|█████████ | 1694/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.166, Acc%=97.00]
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Epoch 1: 90%|█████████ | 1695/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.100, Acc%=97.00]
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Epoch 1: 90%|█████████ | 1696/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0404, Acc%=97.00]
Epoch 1: 91%|█████████ | 1697/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.0404, Acc%=97.00]
Epoch 1: 91%|█████████ | 1697/1875 [00:21<00:02, 77.50it/s, v_num=10, train_loss=0.0732, Acc%=97.00]
Epoch 1: 91%|█████████ | 1698/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.0732, Acc%=97.00]
Epoch 1: 91%|█████████ | 1698/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.117, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1699/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.459, Acc%=97.00]
Epoch 1: 91%|█████████ | 1700/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.459, Acc%=97.00]
Epoch 1: 91%|█████████ | 1700/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.259, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1701/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.223, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1702/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.502, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1703/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.266, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1704/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.098, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1705/1875 [00:21<00:02, 77.51it/s, v_num=10, train_loss=0.128, Acc%=97.00]
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Epoch 1: 91%|█████████ | 1706/1875 [00:22<00:02, 77.51it/s, v_num=10, train_loss=0.0895, Acc%=97.00]
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Epoch 1: 91%|█████████▏| 1711/1875 [00:22<00:02, 77.52it/s, v_num=10, train_loss=0.0354, Acc%=97.00]
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Epoch 1: 91%|█████████▏| 1713/1875 [00:22<00:02, 77.52it/s, v_num=10, train_loss=0.0509, Acc%=97.00]
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Epoch 1: 91%|█████████▏| 1714/1875 [00:22<00:02, 77.51it/s, v_num=10, train_loss=0.0722, Acc%=97.00]
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Epoch 1: 91%|█████████▏| 1715/1875 [00:22<00:02, 77.51it/s, v_num=10, train_loss=0.0723, Acc%=97.00]
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Epoch 1: 95%|█████████▌| 1786/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.414, Acc%=97.00]
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Epoch 1: 95%|█████████▌| 1787/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0663, Acc%=97.00]
Epoch 1: 95%|█████████▌| 1788/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0663, Acc%=97.00]
Epoch 1: 95%|█████████▌| 1788/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0211, Acc%=97.00]
Epoch 1: 95%|█████████▌| 1789/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0211, Acc%=97.00]
Epoch 1: 95%|█████████▌| 1789/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.00876, Acc%=97.00]
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Epoch 1: 95%|█████████▌| 1790/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0257, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1791/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0305, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1792/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0305, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1792/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0433, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1793/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0433, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1793/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.178, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1795/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.344, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1796/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.287, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1797/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.287, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1797/1875 [00:23<00:01, 77.54it/s, v_num=10, train_loss=0.0513, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1798/1875 [00:23<00:00, 77.54it/s, v_num=10, train_loss=0.049, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1799/1875 [00:23<00:00, 77.54it/s, v_num=10, train_loss=0.297, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1800/1875 [00:23<00:00, 77.54it/s, v_num=10, train_loss=0.297, Acc%=97.00]
Epoch 1: 96%|█████████▌| 1800/1875 [00:23<00:00, 77.54it/s, v_num=10, train_loss=0.158, Acc%=97.00]
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Epoch 1: 96%|█████████▌| 1802/1875 [00:23<00:00, 77.54it/s, v_num=10, train_loss=0.283, Acc%=97.00]
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Epoch 1: 100%|██████████| 1875/1875 [00:26<00:00, 69.77it/s, v_num=10, train_loss=0.107, Acc%=97.40]
Epoch 1: 100%|██████████| 1875/1875 [00:26<00:00, 69.77it/s, v_num=10, train_loss=0.107, Acc%=97.40]
Epoch 1: 100%|██████████| 1875/1875 [00:26<00:00, 69.76it/s, v_num=10, train_loss=0.107, Acc%=97.40]
Evaluate the trained model on the test set - pay attention to the cls/Acc metric
perf = trainer.test(routine, dataloaders=[test_dl, ood_dl])
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┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Acc │ 97.440% │
│ Brier │ 0.03890 │
│ Entropy │ 0.07846 │
│ NLL │ 0.07969 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Calibration ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ ECE │ 0.00235 │
│ aECE │ 0.00195 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ OOD Detection ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUPR │ 90.331% │
│ AUROC │ 92.869% │
│ Entropy │ 0.73851 │
│ FPR95 │ 21.660% │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Selective Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUGRC │ 0.136% │
│ AURC │ 0.153% │
│ Cov@5Risk │ 100.000% │
│ Risk@80Cov │ 0.150% │
└──────────────┴───────────────────────────┘
This table provides a lot of information:
OOD Detection: Binary Classification MNIST vs. FashionMNIST - AUPR/AUROC/FPR95: Measures the quality of the OOD detection. The higher the better for AUPR and AUROC, the lower the better for FPR95.
Calibration: Reliability of the Predictions - ECE: Expected Calibration Error. The lower the better. - aECE: Adaptive Expected Calibration Error. The lower the better. (~More precise version of the ECE)
Classification Performance - Accuracy: The ratio of correctly classified images. The higher the better. - Brier: The quality of the predicted probabilities (Mean Squared Error of the predictions vs. ground-truth). The lower the better. - Negative Log-Likelihood: The value of the loss on the test set. The lower the better.
Selective Classification & Grouping Loss - We talk about these points later in the “To go further” section.
3. Training an ensemble of models with TorchUncertainty¶
You have two options here, you can either train the ensemble directly if you have enough memory, otherwise, you can train independent models and do the ensembling during the evaluation (sometimes called inference).
In this case, we will do it sequentially. In this tutorial, you have the choice between training multiple models, which will take time if you have no GPU, or downloading the pre-trained models that we have prepared for you.
Training the ensemble
To train the ensemble, you will have to use the “deep_ensembles” function from TorchUncertainty, which will replicate and change the initialization of your networks to ensure diversity.
from torch_uncertainty.models import deep_ensembles
from torch_uncertainty.transforms import RepeatTarget
# Create the ensemble model
ensemble = deep_ensembles(
LeNet(in_channels=1, num_classes=10),
num_estimators=2,
task="classification",
reset_model_parameters=True,
)
trainer = TUTrainer(accelerator="cpu", max_epochs=1)
ens_routine = ClassificationRoutine(
is_ensemble=True,
num_classes=10,
model=ensemble,
loss=nn.CrossEntropyLoss(), # The loss for the training
format_batch_fn=RepeatTarget(
2
), # How to handle the targets when comparing the predictions
optim_recipe=optim_recipe(
ensemble, 2.0
), # The optimization scheme with the optimizer and the scheduler as a dictionnary
eval_ood=True, # We want to evaluate the OOD-related metrics
)
trainer.fit(ens_routine, train_dataloaders=train_dl, val_dataloaders=test_dl)
ens_perf = trainer.test(ens_routine, dataloaders=[test_dl, ood_dl])
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Epoch 0: 4%|▍ | 82/1875 [00:01<00:29, 60.33it/s, v_num=11, train_loss=2.270]
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Epoch 0: 5%|▍ | 87/1875 [00:01<00:29, 60.39it/s, v_num=11, train_loss=2.280]
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Epoch 0: 6%|▌ | 112/1875 [00:01<00:29, 60.43it/s, v_num=11, train_loss=2.220]
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Epoch 0: 90%|█████████ | 1695/1875 [00:28<00:02, 60.44it/s, v_num=11, train_loss=0.321]
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┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Acc │ 97.000% │
│ Brier │ 0.04723 │
│ Entropy │ 0.16103 │
│ NLL │ 0.10130 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Calibration ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ ECE │ 0.01992 │
│ aECE │ 0.01982 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ OOD Detection ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUPR │ 92.802% │
│ AUROC │ 94.395% │
│ Entropy │ 1.15695 │
│ FPR95 │ 18.960% │
│ ens_Disagre… │ 0.34550 │
│ ens_Entropy │ 1.05367 │
│ ens_MI │ 0.10328 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Selective Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUGRC │ 0.167% │
│ AURC │ 0.183% │
│ Cov@5Risk │ 100.000% │
│ Risk@80Cov │ 0.175% │
└──────────────┴───────────────────────────┘
The results are not comparable since we only trained the ensemble for one epoch to reduce GitHub’s cpu usage. Feel free to run the notebook on your machine for a longer duration.
We need to multiply the learning rate by 2 to account for the fact that we have 4 models in the ensemble and that we average the loss over all the predictions.
#### Downloading the pre-trained models
We have put the pre-trained models on Hugging Face that you can download with the utility function “hf_hub_download” imported just below. These models are trained for 75 epochs and are therefore not comparable to the all the other models trained in this notebook. The pretrained models can be seen on HuggingFace and TorchUncertainty’s are there.
from torch_uncertainty.utils.hub import hf_hub_download
all_models = []
for i in range(8):
hf_hub_download(
repo_id="ENSTA-U2IS/tutorial-models",
filename=f"version_{i}.ckpt",
local_dir="./models/",
)
model = LeNet(in_channels=1, num_classes=10)
state_dict = torch.load(f"./models/version_{i}.ckpt", map_location="cpu")[
"state_dict"
]
state_dict = {k.replace("model.", ""): v for k, v in state_dict.items()}
model.load_state_dict(state_dict)
all_models.append(model)
from torch_uncertainty.models import deep_ensembles
from torch_uncertainty.transforms import RepeatTarget
ensemble = deep_ensembles(
all_models,
num_estimators=None,
task="classification",
reset_model_parameters=True,
)
ens_routine = ClassificationRoutine(
is_ensemble=True,
num_classes=10,
model=ensemble,
loss=nn.CrossEntropyLoss(), # The loss for the training
format_batch_fn=RepeatTarget(
8
), # How to handle the targets when comparing the predictions
optim_recipe=None, # No optim recipe as the model is already trained
eval_ood=True, # We want to evaluate the OOD-related metrics
)
trainer = TUTrainer(accelerator="cpu", max_epochs=max_epochs)
ens_perf = trainer.test(ens_routine, dataloaders=[test_dl, ood_dl])
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┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Acc │ 99.610% │
│ Brier │ 0.00677 │
│ Entropy │ 0.02816 │
│ NLL │ 0.01454 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Calibration ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ ECE │ 0.00459 │
│ aECE │ 0.00451 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ OOD Detection ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUPR │ 98.980% │
│ AUROC │ 99.205% │
│ Entropy │ 1.25233 │
│ FPR95 │ 2.630% │
│ ens_Disagre… │ 0.38779 │
│ ens_Entropy │ 1.01787 │
│ ens_MI │ 0.23446 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Selective Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUGRC │ 0.004% │
│ AURC │ 0.004% │
│ Cov@5Risk │ 100.000% │
│ Risk@80Cov │ 0.000% │
└──────────────┴───────────────────────────┘
4. From Deep Ensembles to Packed-Ensembles¶
In the paper Packed-Ensembles for Efficient Uncertainty Quantification published at the International Conference on Learning Representations (ICLR) in 2023, we introduced a modification of Deep Ensembles to make it more computationally-efficient. The idea is to pack the ensemble members into a single model, which allows us to train the ensemble in a single forward pass. This modification is particularly useful when the ensemble size is large, as it is often the case in practice.
We will need to update the model and replace the layers with their Packed equivalents. You can find the documentation of the Packed-Linear layer using this link, and the Packed-Conv2D, here.
import torch
import torch.nn as nn
from einops import rearrange
from torch_uncertainty.layers import PackedConv2d, PackedLinear
class PackedLeNet(nn.Module):
def __init__(
self,
in_channels: int,
num_classes: int,
alpha: int,
num_estimators: int,
) -> None:
super().__init__()
self.num_estimators = num_estimators
self.conv1 = PackedConv2d(
in_channels,
6,
(5, 5),
alpha=alpha,
num_estimators=num_estimators,
first=True,
)
self.conv2 = PackedConv2d(
6,
16,
(5, 5),
alpha=alpha,
num_estimators=num_estimators,
)
self.pooling = nn.AdaptiveAvgPool2d((4, 4))
self.fc1 = PackedLinear(
256, 120, alpha=alpha, num_estimators=num_estimators
)
self.fc2 = PackedLinear(
120, 84, alpha=alpha, num_estimators=num_estimators
)
self.fc3 = PackedLinear(
84,
num_classes,
alpha=alpha,
num_estimators=num_estimators,
last=True,
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
out = F.relu(self.conv1(x))
out = F.max_pool2d(out, 2)
out = F.relu(self.conv2(out))
out = F.max_pool2d(out, 2)
out = rearrange(
out, "e (m c) h w -> (m e) c h w", m=self.num_estimators
)
out = torch.flatten(out, 1)
out = F.relu(self.fc1(out))
out = F.relu(self.fc2(out))
return self.fc3(out) # Again, no softmax in the model
# Instantiate the model, the images are in grayscale so the number of channels is 1
packed_model = PackedLeNet(
in_channels=1, num_classes=10, alpha=2, num_estimators=4
)
# Create the trainer that will handle the training
trainer = TUTrainer(accelerator="cpu", max_epochs=max_epochs)
# The routine is a wrapper of the model that contains the training logic with the metrics, etc
packed_routine = ClassificationRoutine(
is_ensemble=True,
num_classes=10,
model=packed_model,
loss=nn.CrossEntropyLoss(),
format_batch_fn=RepeatTarget(4),
optim_recipe=optim_recipe(packed_model, 4.0),
eval_ood=True,
)
# In practice, avoid performing the validation on the test set
trainer.fit(packed_routine, train_dataloaders=train_dl, val_dataloaders=test_dl)
packed_perf = trainer.test(packed_routine, dataloaders=[test_dl, ood_dl])
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Epoch 0: 4%|▍ | 78/1875 [00:01<00:33, 54.09it/s, v_num=13, train_loss=2.290]
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Epoch 0: 4%|▍ | 79/1875 [00:01<00:33, 54.11it/s, v_num=13, train_loss=2.270]
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Epoch 0: 4%|▍ | 80/1875 [00:01<00:33, 54.12it/s, v_num=13, train_loss=2.260]
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Epoch 0: 5%|▍ | 85/1875 [00:01<00:33, 54.13it/s, v_num=13, train_loss=2.280]
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Epoch 0: 5%|▍ | 86/1875 [00:01<00:33, 54.14it/s, v_num=13, train_loss=2.290]
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Epoch 0: 5%|▍ | 88/1875 [00:01<00:33, 54.14it/s, v_num=13, train_loss=2.270]
Epoch 0: 5%|▍ | 88/1875 [00:01<00:33, 54.13it/s, v_num=13, train_loss=2.250]
Epoch 0: 5%|▍ | 89/1875 [00:01<00:32, 54.13it/s, v_num=13, train_loss=2.250]
Epoch 0: 5%|▍ | 89/1875 [00:01<00:32, 54.13it/s, v_num=13, train_loss=2.240]
Epoch 0: 5%|▍ | 90/1875 [00:01<00:32, 54.14it/s, v_num=13, train_loss=2.240]
Epoch 0: 5%|▍ | 90/1875 [00:01<00:32, 54.13it/s, v_num=13, train_loss=2.280]
Epoch 0: 5%|▍ | 91/1875 [00:01<00:32, 54.14it/s, v_num=13, train_loss=2.280]
Epoch 0: 5%|▍ | 91/1875 [00:01<00:32, 54.13it/s, v_num=13, train_loss=2.320]
Epoch 0: 5%|▍ | 92/1875 [00:01<00:32, 54.15it/s, v_num=13, train_loss=2.320]
Epoch 0: 5%|▍ | 92/1875 [00:01<00:32, 54.14it/s, v_num=13, train_loss=2.260]
Epoch 0: 5%|▍ | 93/1875 [00:01<00:32, 54.16it/s, v_num=13, train_loss=2.260]
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Epoch 0: 6%|▌ | 111/1875 [00:02<00:32, 54.18it/s, v_num=13, train_loss=2.220]
Epoch 0: 6%|▌ | 112/1875 [00:02<00:32, 54.19it/s, v_num=13, train_loss=2.220]
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Epoch 0: 6%|▌ | 117/1875 [00:02<00:32, 54.22it/s, v_num=13, train_loss=2.220]
Epoch 0: 6%|▌ | 117/1875 [00:02<00:32, 54.21it/s, v_num=13, train_loss=2.250]
Epoch 0: 6%|▋ | 118/1875 [00:02<00:32, 54.23it/s, v_num=13, train_loss=2.250]
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Epoch 0: 7%|▋ | 137/1875 [00:02<00:32, 54.24it/s, v_num=13, train_loss=2.180]
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Epoch 0: 91%|█████████ | 1706/1875 [00:31<00:03, 54.33it/s, v_num=13, train_loss=0.462]
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Epoch 0: 91%|█████████ | 1708/1875 [00:31<00:03, 54.33it/s, v_num=13, train_loss=0.378]
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Epoch 0: 95%|█████████▍| 1781/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.262]
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Epoch 0: 95%|█████████▌| 1782/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.140]
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Epoch 0: 95%|█████████▌| 1783/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.289]
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Epoch 0: 95%|█████████▌| 1784/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.258]
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Epoch 0: 95%|█████████▌| 1785/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.230]
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Epoch 0: 95%|█████████▌| 1786/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.345]
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Epoch 0: 95%|█████████▌| 1789/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.781]
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Epoch 0: 95%|█████████▌| 1790/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.300]
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Epoch 0: 96%|█████████▌| 1791/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.328]
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Epoch 0: 96%|█████████▌| 1792/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.603]
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Epoch 0: 96%|█████████▌| 1793/1875 [00:32<00:01, 54.35it/s, v_num=13, train_loss=0.280]
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Epoch 0: 96%|█████████▌| 1794/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.286]
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Epoch 0: 96%|█████████▌| 1795/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.196]
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Epoch 0: 96%|█████████▌| 1796/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.199]
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Epoch 0: 96%|█████████▌| 1797/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.406]
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Epoch 0: 96%|█████████▌| 1798/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.205]
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Epoch 0: 96%|█████████▌| 1799/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.317]
Epoch 0: 96%|█████████▌| 1800/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.317]
Epoch 0: 96%|█████████▌| 1800/1875 [00:33<00:01, 54.35it/s, v_num=13, train_loss=0.510]
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Epoch 0: 96%|█████████▋| 1807/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.101]
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Epoch 0: 96%|█████████▋| 1808/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.172]
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Epoch 0: 96%|█████████▋| 1809/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.324]
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Epoch 0: 97%|█████████▋| 1810/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.160]
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Epoch 0: 97%|█████████▋| 1811/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.180]
Epoch 0: 97%|█████████▋| 1812/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.180]
Epoch 0: 97%|█████████▋| 1812/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.248]
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Epoch 0: 97%|█████████▋| 1815/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.474]
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Epoch 0: 97%|█████████▋| 1816/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.433]
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Epoch 0: 97%|█████████▋| 1817/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.112]
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Epoch 0: 97%|█████████▋| 1818/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.365]
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Epoch 0: 97%|█████████▋| 1819/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.316]
Epoch 0: 97%|█████████▋| 1820/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.316]
Epoch 0: 97%|█████████▋| 1820/1875 [00:33<00:01, 54.36it/s, v_num=13, train_loss=0.198]
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Epoch 0: 97%|█████████▋| 1821/1875 [00:33<00:00, 54.36it/s, v_num=13, train_loss=0.380]
Epoch 0: 97%|█████████▋| 1822/1875 [00:33<00:00, 54.36it/s, v_num=13, train_loss=0.380]
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Epoch 0: 97%|█████████▋| 1824/1875 [00:33<00:00, 54.36it/s, v_num=13, train_loss=0.145]
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Epoch 0: 97%|█████████▋| 1827/1875 [00:33<00:00, 54.37it/s, v_num=13, train_loss=0.142]
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Epoch 0: 98%|█████████▊| 1830/1875 [00:33<00:00, 54.37it/s, v_num=13, train_loss=0.191]
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Epoch 0: 98%|█████████▊| 1831/1875 [00:33<00:00, 54.37it/s, v_num=13, train_loss=0.201]
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Epoch 1: 2%|▏ | 33/1875 [00:00<00:33, 54.57it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 2%|▏ | 34/1875 [00:00<00:33, 54.61it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 2%|▏ | 34/1875 [00:00<00:33, 54.59it/s, v_num=13, train_loss=0.357, Acc%=96.40]
Epoch 1: 2%|▏ | 35/1875 [00:00<00:33, 54.66it/s, v_num=13, train_loss=0.357, Acc%=96.40]
Epoch 1: 2%|▏ | 35/1875 [00:00<00:33, 54.64it/s, v_num=13, train_loss=0.295, Acc%=96.40]
Epoch 1: 2%|▏ | 36/1875 [00:00<00:33, 54.69it/s, v_num=13, train_loss=0.295, Acc%=96.40]
Epoch 1: 2%|▏ | 36/1875 [00:00<00:33, 54.67it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 2%|▏ | 37/1875 [00:00<00:33, 54.69it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 2%|▏ | 37/1875 [00:00<00:33, 54.67it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 2%|▏ | 38/1875 [00:00<00:33, 54.70it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 2%|▏ | 38/1875 [00:00<00:33, 54.68it/s, v_num=13, train_loss=0.328, Acc%=96.40]
Epoch 1: 2%|▏ | 39/1875 [00:00<00:33, 54.73it/s, v_num=13, train_loss=0.328, Acc%=96.40]
Epoch 1: 2%|▏ | 39/1875 [00:00<00:33, 54.72it/s, v_num=13, train_loss=0.223, Acc%=96.40]
Epoch 1: 2%|▏ | 40/1875 [00:00<00:33, 54.76it/s, v_num=13, train_loss=0.223, Acc%=96.40]
Epoch 1: 2%|▏ | 40/1875 [00:00<00:33, 54.74it/s, v_num=13, train_loss=0.332, Acc%=96.40]
Epoch 1: 2%|▏ | 41/1875 [00:00<00:33, 54.78it/s, v_num=13, train_loss=0.332, Acc%=96.40]
Epoch 1: 2%|▏ | 41/1875 [00:00<00:33, 54.77it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 2%|▏ | 42/1875 [00:00<00:33, 54.79it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 2%|▏ | 42/1875 [00:00<00:33, 54.77it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 2%|▏ | 43/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 2%|▏ | 43/1875 [00:00<00:33, 54.80it/s, v_num=13, train_loss=0.246, Acc%=96.40]
Epoch 1: 2%|▏ | 44/1875 [00:00<00:33, 54.83it/s, v_num=13, train_loss=0.246, Acc%=96.40]
Epoch 1: 2%|▏ | 44/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 2%|▏ | 45/1875 [00:00<00:33, 54.83it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 2%|▏ | 45/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.290, Acc%=96.40]
Epoch 1: 2%|▏ | 46/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.290, Acc%=96.40]
Epoch 1: 2%|▏ | 46/1875 [00:00<00:33, 54.79it/s, v_num=13, train_loss=0.227, Acc%=96.40]
Epoch 1: 3%|▎ | 47/1875 [00:00<00:33, 54.80it/s, v_num=13, train_loss=0.227, Acc%=96.40]
Epoch 1: 3%|▎ | 47/1875 [00:00<00:33, 54.78it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 3%|▎ | 48/1875 [00:00<00:33, 54.79it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 3%|▎ | 48/1875 [00:00<00:33, 54.78it/s, v_num=13, train_loss=0.248, Acc%=96.40]
Epoch 1: 3%|▎ | 49/1875 [00:00<00:33, 54.80it/s, v_num=13, train_loss=0.248, Acc%=96.40]
Epoch 1: 3%|▎ | 49/1875 [00:00<00:33, 54.79it/s, v_num=13, train_loss=0.303, Acc%=96.40]
Epoch 1: 3%|▎ | 50/1875 [00:00<00:33, 54.82it/s, v_num=13, train_loss=0.303, Acc%=96.40]
Epoch 1: 3%|▎ | 50/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.424, Acc%=96.40]
Epoch 1: 3%|▎ | 51/1875 [00:00<00:33, 54.83it/s, v_num=13, train_loss=0.424, Acc%=96.40]
Epoch 1: 3%|▎ | 51/1875 [00:00<00:33, 54.81it/s, v_num=13, train_loss=0.283, Acc%=96.40]
Epoch 1: 3%|▎ | 52/1875 [00:00<00:33, 54.84it/s, v_num=13, train_loss=0.283, Acc%=96.40]
Epoch 1: 3%|▎ | 52/1875 [00:00<00:33, 54.82it/s, v_num=13, train_loss=0.714, Acc%=96.40]
Epoch 1: 3%|▎ | 53/1875 [00:00<00:33, 54.86it/s, v_num=13, train_loss=0.714, Acc%=96.40]
Epoch 1: 3%|▎ | 53/1875 [00:00<00:33, 54.85it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 3%|▎ | 54/1875 [00:00<00:33, 54.77it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 3%|▎ | 54/1875 [00:00<00:33, 54.75it/s, v_num=13, train_loss=0.747, Acc%=96.40]
Epoch 1: 3%|▎ | 55/1875 [00:01<00:33, 54.77it/s, v_num=13, train_loss=0.747, Acc%=96.40]
Epoch 1: 3%|▎ | 55/1875 [00:01<00:33, 54.76it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 3%|▎ | 56/1875 [00:01<00:33, 54.79it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 3%|▎ | 56/1875 [00:01<00:33, 54.78it/s, v_num=13, train_loss=0.222, Acc%=96.40]
Epoch 1: 3%|▎ | 57/1875 [00:01<00:33, 54.80it/s, v_num=13, train_loss=0.222, Acc%=96.40]
Epoch 1: 3%|▎ | 57/1875 [00:01<00:33, 54.79it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 3%|▎ | 58/1875 [00:01<00:33, 54.81it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 3%|▎ | 58/1875 [00:01<00:33, 54.80it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 3%|▎ | 59/1875 [00:01<00:33, 54.82it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 3%|▎ | 59/1875 [00:01<00:33, 54.81it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 3%|▎ | 60/1875 [00:01<00:33, 54.85it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 3%|▎ | 60/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 3%|▎ | 61/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 3%|▎ | 61/1875 [00:01<00:33, 54.83it/s, v_num=13, train_loss=0.323, Acc%=96.40]
Epoch 1: 3%|▎ | 62/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.323, Acc%=96.40]
Epoch 1: 3%|▎ | 62/1875 [00:01<00:33, 54.83it/s, v_num=13, train_loss=0.438, Acc%=96.40]
Epoch 1: 3%|▎ | 63/1875 [00:01<00:33, 54.86it/s, v_num=13, train_loss=0.438, Acc%=96.40]
Epoch 1: 3%|▎ | 63/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.364, Acc%=96.40]
Epoch 1: 3%|▎ | 64/1875 [00:01<00:33, 54.85it/s, v_num=13, train_loss=0.364, Acc%=96.40]
Epoch 1: 3%|▎ | 64/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 3%|▎ | 65/1875 [00:01<00:33, 54.84it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 3%|▎ | 65/1875 [00:01<00:33, 54.83it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 4%|▎ | 66/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 4%|▎ | 66/1875 [00:01<00:32, 54.84it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 4%|▎ | 67/1875 [00:01<00:32, 54.86it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 4%|▎ | 67/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.327, Acc%=96.40]
Epoch 1: 4%|▎ | 68/1875 [00:01<00:32, 54.86it/s, v_num=13, train_loss=0.327, Acc%=96.40]
Epoch 1: 4%|▎ | 68/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 4%|▎ | 69/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 4%|▎ | 69/1875 [00:01<00:32, 54.84it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 4%|▎ | 70/1875 [00:01<00:32, 54.83it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 4%|▎ | 70/1875 [00:01<00:32, 54.81it/s, v_num=13, train_loss=0.123, Acc%=96.40]
Epoch 1: 4%|▍ | 71/1875 [00:01<00:32, 54.81it/s, v_num=13, train_loss=0.123, Acc%=96.40]
Epoch 1: 4%|▍ | 71/1875 [00:01<00:32, 54.80it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 4%|▍ | 72/1875 [00:01<00:32, 54.82it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 4%|▍ | 72/1875 [00:01<00:32, 54.81it/s, v_num=13, train_loss=0.644, Acc%=96.40]
Epoch 1: 4%|▍ | 73/1875 [00:01<00:32, 54.82it/s, v_num=13, train_loss=0.644, Acc%=96.40]
Epoch 1: 4%|▍ | 73/1875 [00:01<00:32, 54.81it/s, v_num=13, train_loss=0.439, Acc%=96.40]
Epoch 1: 4%|▍ | 74/1875 [00:01<00:32, 54.83it/s, v_num=13, train_loss=0.439, Acc%=96.40]
Epoch 1: 4%|▍ | 74/1875 [00:01<00:32, 54.81it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 4%|▍ | 75/1875 [00:01<00:32, 54.83it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 4%|▍ | 75/1875 [00:01<00:32, 54.82it/s, v_num=13, train_loss=0.230, Acc%=96.40]
Epoch 1: 4%|▍ | 76/1875 [00:01<00:32, 54.83it/s, v_num=13, train_loss=0.230, Acc%=96.40]
Epoch 1: 4%|▍ | 76/1875 [00:01<00:32, 54.82it/s, v_num=13, train_loss=0.394, Acc%=96.40]
Epoch 1: 4%|▍ | 77/1875 [00:01<00:32, 54.84it/s, v_num=13, train_loss=0.394, Acc%=96.40]
Epoch 1: 4%|▍ | 77/1875 [00:01<00:32, 54.83it/s, v_num=13, train_loss=0.170, Acc%=96.40]
Epoch 1: 4%|▍ | 78/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.170, Acc%=96.40]
Epoch 1: 4%|▍ | 78/1875 [00:01<00:32, 54.84it/s, v_num=13, train_loss=0.305, Acc%=96.40]
Epoch 1: 4%|▍ | 79/1875 [00:01<00:32, 54.86it/s, v_num=13, train_loss=0.305, Acc%=96.40]
Epoch 1: 4%|▍ | 79/1875 [00:01<00:32, 54.85it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 4%|▍ | 80/1875 [00:01<00:32, 54.88it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 4%|▍ | 80/1875 [00:01<00:32, 54.87it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 4%|▍ | 81/1875 [00:01<00:32, 54.88it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 4%|▍ | 81/1875 [00:01<00:32, 54.87it/s, v_num=13, train_loss=0.345, Acc%=96.40]
Epoch 1: 4%|▍ | 82/1875 [00:01<00:32, 54.88it/s, v_num=13, train_loss=0.345, Acc%=96.40]
Epoch 1: 4%|▍ | 82/1875 [00:01<00:32, 54.87it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 4%|▍ | 83/1875 [00:01<00:32, 54.89it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 4%|▍ | 83/1875 [00:01<00:32, 54.88it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 4%|▍ | 84/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 4%|▍ | 84/1875 [00:01<00:32, 54.89it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 5%|▍ | 85/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 5%|▍ | 85/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.306, Acc%=96.40]
Epoch 1: 5%|▍ | 86/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.306, Acc%=96.40]
Epoch 1: 5%|▍ | 86/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.413, Acc%=96.40]
Epoch 1: 5%|▍ | 87/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.413, Acc%=96.40]
Epoch 1: 5%|▍ | 87/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 5%|▍ | 88/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 5%|▍ | 88/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.276, Acc%=96.40]
Epoch 1: 5%|▍ | 89/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.276, Acc%=96.40]
Epoch 1: 5%|▍ | 89/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 5%|▍ | 90/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 5%|▍ | 90/1875 [00:01<00:32, 54.89it/s, v_num=13, train_loss=0.463, Acc%=96.40]
Epoch 1: 5%|▍ | 91/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.463, Acc%=96.40]
Epoch 1: 5%|▍ | 91/1875 [00:01<00:32, 54.89it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 5%|▍ | 92/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 5%|▍ | 92/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 5%|▍ | 93/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 5%|▍ | 93/1875 [00:01<00:32, 54.90it/s, v_num=13, train_loss=0.422, Acc%=96.40]
Epoch 1: 5%|▌ | 94/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.422, Acc%=96.40]
Epoch 1: 5%|▌ | 94/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.271, Acc%=96.40]
Epoch 1: 5%|▌ | 95/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.271, Acc%=96.40]
Epoch 1: 5%|▌ | 95/1875 [00:01<00:32, 54.91it/s, v_num=13, train_loss=0.490, Acc%=96.40]
Epoch 1: 5%|▌ | 96/1875 [00:01<00:32, 54.93it/s, v_num=13, train_loss=0.490, Acc%=96.40]
Epoch 1: 5%|▌ | 96/1875 [00:01<00:32, 54.92it/s, v_num=13, train_loss=0.515, Acc%=96.40]
Epoch 1: 5%|▌ | 97/1875 [00:01<00:32, 54.94it/s, v_num=13, train_loss=0.515, Acc%=96.40]
Epoch 1: 5%|▌ | 97/1875 [00:01<00:32, 54.93it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 5%|▌ | 98/1875 [00:01<00:32, 54.95it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 5%|▌ | 98/1875 [00:01<00:32, 54.94it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 5%|▌ | 99/1875 [00:01<00:32, 54.95it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 5%|▌ | 99/1875 [00:01<00:32, 54.95it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 5%|▌ | 100/1875 [00:01<00:32, 54.96it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 5%|▌ | 100/1875 [00:01<00:32, 54.95it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 5%|▌ | 101/1875 [00:01<00:32, 54.96it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 5%|▌ | 101/1875 [00:01<00:32, 54.95it/s, v_num=13, train_loss=0.322, Acc%=96.40]
Epoch 1: 5%|▌ | 102/1875 [00:01<00:32, 54.97it/s, v_num=13, train_loss=0.322, Acc%=96.40]
Epoch 1: 5%|▌ | 102/1875 [00:01<00:32, 54.96it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 5%|▌ | 103/1875 [00:01<00:32, 54.97it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 5%|▌ | 103/1875 [00:01<00:32, 54.96it/s, v_num=13, train_loss=0.249, Acc%=96.40]
Epoch 1: 6%|▌ | 104/1875 [00:01<00:32, 54.98it/s, v_num=13, train_loss=0.249, Acc%=96.40]
Epoch 1: 6%|▌ | 104/1875 [00:01<00:32, 54.97it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 6%|▌ | 105/1875 [00:01<00:32, 54.98it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 6%|▌ | 105/1875 [00:01<00:32, 54.97it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 6%|▌ | 106/1875 [00:01<00:32, 54.99it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 6%|▌ | 106/1875 [00:01<00:32, 54.98it/s, v_num=13, train_loss=0.307, Acc%=96.40]
Epoch 1: 6%|▌ | 107/1875 [00:01<00:32, 54.99it/s, v_num=13, train_loss=0.307, Acc%=96.40]
Epoch 1: 6%|▌ | 107/1875 [00:01<00:32, 54.99it/s, v_num=13, train_loss=0.763, Acc%=96.40]
Epoch 1: 6%|▌ | 108/1875 [00:01<00:32, 55.01it/s, v_num=13, train_loss=0.763, Acc%=96.40]
Epoch 1: 6%|▌ | 108/1875 [00:01<00:32, 55.00it/s, v_num=13, train_loss=0.489, Acc%=96.40]
Epoch 1: 6%|▌ | 109/1875 [00:01<00:32, 55.01it/s, v_num=13, train_loss=0.489, Acc%=96.40]
Epoch 1: 6%|▌ | 109/1875 [00:01<00:32, 55.01it/s, v_num=13, train_loss=0.194, Acc%=96.40]
Epoch 1: 6%|▌ | 110/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.194, Acc%=96.40]
Epoch 1: 6%|▌ | 110/1875 [00:02<00:32, 54.98it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 6%|▌ | 111/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 6%|▌ | 111/1875 [00:02<00:32, 54.98it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 6%|▌ | 112/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 6%|▌ | 112/1875 [00:02<00:32, 54.98it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 6%|▌ | 113/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 6%|▌ | 113/1875 [00:02<00:32, 54.98it/s, v_num=13, train_loss=0.377, Acc%=96.40]
Epoch 1: 6%|▌ | 114/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.377, Acc%=96.40]
Epoch 1: 6%|▌ | 114/1875 [00:02<00:32, 54.99it/s, v_num=13, train_loss=0.194, Acc%=96.40]
Epoch 1: 6%|▌ | 115/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.194, Acc%=96.40]
Epoch 1: 6%|▌ | 115/1875 [00:02<00:32, 55.00it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 6%|▌ | 116/1875 [00:02<00:31, 55.00it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 6%|▌ | 116/1875 [00:02<00:31, 54.99it/s, v_num=13, train_loss=0.349, Acc%=96.40]
Epoch 1: 6%|▌ | 117/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.349, Acc%=96.40]
Epoch 1: 6%|▌ | 117/1875 [00:02<00:31, 55.00it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 6%|▋ | 118/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 6%|▋ | 118/1875 [00:02<00:31, 55.00it/s, v_num=13, train_loss=0.447, Acc%=96.40]
Epoch 1: 6%|▋ | 119/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.447, Acc%=96.40]
Epoch 1: 6%|▋ | 119/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 6%|▋ | 120/1875 [00:02<00:31, 55.02it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 6%|▋ | 120/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.327, Acc%=96.40]
Epoch 1: 6%|▋ | 121/1875 [00:02<00:31, 55.02it/s, v_num=13, train_loss=0.327, Acc%=96.40]
Epoch 1: 6%|▋ | 121/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.326, Acc%=96.40]
Epoch 1: 7%|▋ | 122/1875 [00:02<00:31, 55.02it/s, v_num=13, train_loss=0.326, Acc%=96.40]
Epoch 1: 7%|▋ | 122/1875 [00:02<00:31, 55.01it/s, v_num=13, train_loss=0.107, Acc%=96.40]
Epoch 1: 7%|▋ | 123/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.107, Acc%=96.40]
Epoch 1: 7%|▋ | 123/1875 [00:02<00:31, 55.02it/s, v_num=13, train_loss=0.569, Acc%=96.40]
Epoch 1: 7%|▋ | 124/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.569, Acc%=96.40]
Epoch 1: 7%|▋ | 124/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 7%|▋ | 125/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 7%|▋ | 125/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.137, Acc%=96.40]
Epoch 1: 7%|▋ | 126/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.137, Acc%=96.40]
Epoch 1: 7%|▋ | 126/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 7%|▋ | 127/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 7%|▋ | 127/1875 [00:02<00:31, 55.02it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 7%|▋ | 128/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 7%|▋ | 128/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 7%|▋ | 129/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 7%|▋ | 129/1875 [00:02<00:31, 55.03it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 7%|▋ | 130/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 7%|▋ | 130/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 7%|▋ | 131/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 7%|▋ | 131/1875 [00:02<00:31, 55.04it/s, v_num=13, train_loss=0.304, Acc%=96.40]
Epoch 1: 7%|▋ | 132/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.304, Acc%=96.40]
Epoch 1: 7%|▋ | 132/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.466, Acc%=96.40]
Epoch 1: 7%|▋ | 133/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.466, Acc%=96.40]
Epoch 1: 7%|▋ | 133/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.235, Acc%=96.40]
Epoch 1: 7%|▋ | 134/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.235, Acc%=96.40]
Epoch 1: 7%|▋ | 134/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 7%|▋ | 135/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 7%|▋ | 135/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 7%|▋ | 136/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 7%|▋ | 136/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.256, Acc%=96.40]
Epoch 1: 7%|▋ | 137/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.256, Acc%=96.40]
Epoch 1: 7%|▋ | 137/1875 [00:02<00:31, 55.05it/s, v_num=13, train_loss=0.245, Acc%=96.40]
Epoch 1: 7%|▋ | 138/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.245, Acc%=96.40]
Epoch 1: 7%|▋ | 138/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 7%|▋ | 139/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 7%|▋ | 139/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 7%|▋ | 140/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 7%|▋ | 140/1875 [00:02<00:31, 55.06it/s, v_num=13, train_loss=0.236, Acc%=96.40]
Epoch 1: 8%|▊ | 141/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.236, Acc%=96.40]
Epoch 1: 8%|▊ | 141/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.324, Acc%=96.40]
Epoch 1: 8%|▊ | 142/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.324, Acc%=96.40]
Epoch 1: 8%|▊ | 142/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 8%|▊ | 143/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 8%|▊ | 143/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.0898, Acc%=96.40]
Epoch 1: 8%|▊ | 144/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.0898, Acc%=96.40]
Epoch 1: 8%|▊ | 144/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.220, Acc%=96.40]
Epoch 1: 8%|▊ | 145/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.220, Acc%=96.40]
Epoch 1: 8%|▊ | 145/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.481, Acc%=96.40]
Epoch 1: 8%|▊ | 146/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.481, Acc%=96.40]
Epoch 1: 8%|▊ | 146/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.0986, Acc%=96.40]
Epoch 1: 8%|▊ | 147/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.0986, Acc%=96.40]
Epoch 1: 8%|▊ | 147/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.157, Acc%=96.40]
Epoch 1: 8%|▊ | 148/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.157, Acc%=96.40]
Epoch 1: 8%|▊ | 148/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.219, Acc%=96.40]
Epoch 1: 8%|▊ | 149/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.219, Acc%=96.40]
Epoch 1: 8%|▊ | 149/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.108, Acc%=96.40]
Epoch 1: 8%|▊ | 150/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.108, Acc%=96.40]
Epoch 1: 8%|▊ | 150/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.188, Acc%=96.40]
Epoch 1: 8%|▊ | 151/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.188, Acc%=96.40]
Epoch 1: 8%|▊ | 151/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.182, Acc%=96.40]
Epoch 1: 8%|▊ | 152/1875 [00:02<00:31, 55.09it/s, v_num=13, train_loss=0.182, Acc%=96.40]
Epoch 1: 8%|▊ | 152/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.304, Acc%=96.40]
Epoch 1: 8%|▊ | 153/1875 [00:02<00:31, 55.09it/s, v_num=13, train_loss=0.304, Acc%=96.40]
Epoch 1: 8%|▊ | 153/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.768, Acc%=96.40]
Epoch 1: 8%|▊ | 154/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.768, Acc%=96.40]
Epoch 1: 8%|▊ | 154/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.262, Acc%=96.40]
Epoch 1: 8%|▊ | 155/1875 [00:02<00:31, 55.09it/s, v_num=13, train_loss=0.262, Acc%=96.40]
Epoch 1: 8%|▊ | 155/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.281, Acc%=96.40]
Epoch 1: 8%|▊ | 156/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.281, Acc%=96.40]
Epoch 1: 8%|▊ | 156/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.0547, Acc%=96.40]
Epoch 1: 8%|▊ | 157/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.0547, Acc%=96.40]
Epoch 1: 8%|▊ | 157/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 8%|▊ | 158/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 8%|▊ | 158/1875 [00:02<00:31, 55.07it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 8%|▊ | 159/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 8%|▊ | 159/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 9%|▊ | 160/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 9%|▊ | 160/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 9%|▊ | 161/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 9%|▊ | 161/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 9%|▊ | 162/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 9%|▊ | 162/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 9%|▊ | 163/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 9%|▊ | 163/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.294, Acc%=96.40]
Epoch 1: 9%|▊ | 164/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.294, Acc%=96.40]
Epoch 1: 9%|▊ | 164/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.382, Acc%=96.40]
Epoch 1: 9%|▉ | 165/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.382, Acc%=96.40]
Epoch 1: 9%|▉ | 165/1875 [00:02<00:31, 55.08it/s, v_num=13, train_loss=0.294, Acc%=96.40]
Epoch 1: 9%|▉ | 166/1875 [00:03<00:31, 55.06it/s, v_num=13, train_loss=0.294, Acc%=96.40]
Epoch 1: 9%|▉ | 166/1875 [00:03<00:31, 55.06it/s, v_num=13, train_loss=0.208, Acc%=96.40]
Epoch 1: 9%|▉ | 167/1875 [00:03<00:31, 55.06it/s, v_num=13, train_loss=0.208, Acc%=96.40]
Epoch 1: 9%|▉ | 167/1875 [00:03<00:31, 55.05it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 9%|▉ | 168/1875 [00:03<00:31, 55.05it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 9%|▉ | 168/1875 [00:03<00:31, 55.05it/s, v_num=13, train_loss=0.248, Acc%=96.40]
Epoch 1: 9%|▉ | 169/1875 [00:03<00:30, 55.06it/s, v_num=13, train_loss=0.248, Acc%=96.40]
Epoch 1: 9%|▉ | 169/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.285, Acc%=96.40]
Epoch 1: 9%|▉ | 170/1875 [00:03<00:30, 55.06it/s, v_num=13, train_loss=0.285, Acc%=96.40]
Epoch 1: 9%|▉ | 170/1875 [00:03<00:30, 55.06it/s, v_num=13, train_loss=0.235, Acc%=96.40]
Epoch 1: 9%|▉ | 171/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.235, Acc%=96.40]
Epoch 1: 9%|▉ | 171/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.0917, Acc%=96.40]
Epoch 1: 9%|▉ | 172/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.0917, Acc%=96.40]
Epoch 1: 9%|▉ | 172/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.130, Acc%=96.40]
Epoch 1: 9%|▉ | 173/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.130, Acc%=96.40]
Epoch 1: 9%|▉ | 173/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.384, Acc%=96.40]
Epoch 1: 9%|▉ | 174/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.384, Acc%=96.40]
Epoch 1: 9%|▉ | 174/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.221, Acc%=96.40]
Epoch 1: 9%|▉ | 175/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.221, Acc%=96.40]
Epoch 1: 9%|▉ | 175/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 9%|▉ | 176/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 9%|▉ | 176/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 9%|▉ | 177/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 9%|▉ | 177/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.513, Acc%=96.40]
Epoch 1: 9%|▉ | 178/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.513, Acc%=96.40]
Epoch 1: 9%|▉ | 178/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 10%|▉ | 179/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 10%|▉ | 179/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.128, Acc%=96.40]
Epoch 1: 10%|▉ | 180/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.128, Acc%=96.40]
Epoch 1: 10%|▉ | 180/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 10%|▉ | 181/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 10%|▉ | 181/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.244, Acc%=96.40]
Epoch 1: 10%|▉ | 182/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.244, Acc%=96.40]
Epoch 1: 10%|▉ | 182/1875 [00:03<00:30, 55.03it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 10%|▉ | 183/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 10%|▉ | 183/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 10%|▉ | 184/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 10%|▉ | 184/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.536, Acc%=96.40]
Epoch 1: 10%|▉ | 185/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.536, Acc%=96.40]
Epoch 1: 10%|▉ | 185/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.528, Acc%=96.40]
Epoch 1: 10%|▉ | 186/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.528, Acc%=96.40]
Epoch 1: 10%|▉ | 186/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.176, Acc%=96.40]
Epoch 1: 10%|▉ | 187/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.176, Acc%=96.40]
Epoch 1: 10%|▉ | 187/1875 [00:03<00:30, 55.04it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 10%|█ | 188/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 10%|█ | 188/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.402, Acc%=96.40]
Epoch 1: 10%|█ | 189/1875 [00:03<00:30, 55.05it/s, v_num=13, train_loss=0.402, Acc%=96.40]
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Epoch 1: 10%|█ | 195/1875 [00:03<00:30, 55.07it/s, v_num=13, train_loss=0.340, Acc%=96.40]
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Epoch 1: 10%|█ | 196/1875 [00:03<00:30, 55.07it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 11%|█ | 197/1875 [00:03<00:30, 55.08it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 11%|█ | 197/1875 [00:03<00:30, 55.08it/s, v_num=13, train_loss=0.333, Acc%=96.40]
Epoch 1: 11%|█ | 198/1875 [00:03<00:30, 55.09it/s, v_num=13, train_loss=0.333, Acc%=96.40]
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Epoch 1: 11%|█ | 200/1875 [00:03<00:30, 55.08it/s, v_num=13, train_loss=0.587, Acc%=96.40]
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Epoch 1: 11%|█ | 208/1875 [00:03<00:30, 55.08it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 11%|█ | 208/1875 [00:03<00:30, 55.07it/s, v_num=13, train_loss=0.321, Acc%=96.40]
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Epoch 1: 12%|█▏ | 223/1875 [00:04<00:30, 55.05it/s, v_num=13, train_loss=0.255, Acc%=96.40]
Epoch 1: 12%|█▏ | 224/1875 [00:04<00:29, 55.05it/s, v_num=13, train_loss=0.255, Acc%=96.40]
Epoch 1: 12%|█▏ | 224/1875 [00:04<00:29, 55.05it/s, v_num=13, train_loss=0.282, Acc%=96.40]
Epoch 1: 12%|█▏ | 225/1875 [00:04<00:29, 55.05it/s, v_num=13, train_loss=0.282, Acc%=96.40]
Epoch 1: 12%|█▏ | 225/1875 [00:04<00:29, 55.04it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 12%|█▏ | 226/1875 [00:04<00:29, 55.03it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 12%|█▏ | 226/1875 [00:04<00:29, 55.03it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 12%|█▏ | 227/1875 [00:04<00:29, 55.02it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 12%|█▏ | 227/1875 [00:04<00:29, 55.01it/s, v_num=13, train_loss=0.453, Acc%=96.40]
Epoch 1: 12%|█▏ | 228/1875 [00:04<00:29, 54.99it/s, v_num=13, train_loss=0.453, Acc%=96.40]
Epoch 1: 12%|█▏ | 228/1875 [00:04<00:29, 54.99it/s, v_num=13, train_loss=0.567, Acc%=96.40]
Epoch 1: 12%|█▏ | 229/1875 [00:04<00:29, 54.99it/s, v_num=13, train_loss=0.567, Acc%=96.40]
Epoch 1: 12%|█▏ | 229/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 12%|█▏ | 230/1875 [00:04<00:29, 54.99it/s, v_num=13, train_loss=0.168, Acc%=96.40]
Epoch 1: 12%|█▏ | 230/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 12%|█▏ | 231/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 12%|█▏ | 231/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.217, Acc%=96.40]
Epoch 1: 12%|█▏ | 232/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.217, Acc%=96.40]
Epoch 1: 12%|█▏ | 232/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.410, Acc%=96.40]
Epoch 1: 12%|█▏ | 233/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.410, Acc%=96.40]
Epoch 1: 12%|█▏ | 233/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 12%|█▏ | 234/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 12%|█▏ | 234/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.381, Acc%=96.40]
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Epoch 1: 13%|█▎ | 235/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 13%|█▎ | 236/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 13%|█▎ | 236/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.300, Acc%=96.40]
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Epoch 1: 13%|█▎ | 237/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 13%|█▎ | 238/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 13%|█▎ | 238/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.145, Acc%=96.40]
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Epoch 1: 13%|█▎ | 239/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.440, Acc%=96.40]
Epoch 1: 13%|█▎ | 240/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.440, Acc%=96.40]
Epoch 1: 13%|█▎ | 240/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.246, Acc%=96.40]
Epoch 1: 13%|█▎ | 241/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.246, Acc%=96.40]
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Epoch 1: 14%|█▎ | 255/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.219, Acc%=96.40]
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Epoch 1: 14%|█▎ | 256/1875 [00:04<00:29, 54.98it/s, v_num=13, train_loss=0.263, Acc%=96.40]
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Epoch 1: 14%|█▍ | 266/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.149, Acc%=96.40]
Epoch 1: 14%|█▍ | 266/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.495, Acc%=96.40]
Epoch 1: 14%|█▍ | 267/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.495, Acc%=96.40]
Epoch 1: 14%|█▍ | 267/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 14%|█▍ | 268/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 14%|█▍ | 268/1875 [00:04<00:29, 54.95it/s, v_num=13, train_loss=0.307, Acc%=96.40]
Epoch 1: 14%|█▍ | 269/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.307, Acc%=96.40]
Epoch 1: 14%|█▍ | 269/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.344, Acc%=96.40]
Epoch 1: 14%|█▍ | 270/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.344, Acc%=96.40]
Epoch 1: 14%|█▍ | 270/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.558, Acc%=96.40]
Epoch 1: 14%|█▍ | 271/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.558, Acc%=96.40]
Epoch 1: 14%|█▍ | 271/1875 [00:04<00:29, 54.96it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 15%|█▍ | 272/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 15%|█▍ | 272/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.180, Acc%=96.40]
Epoch 1: 15%|█▍ | 273/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.180, Acc%=96.40]
Epoch 1: 15%|█▍ | 273/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.358, Acc%=96.40]
Epoch 1: 15%|█▍ | 274/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.358, Acc%=96.40]
Epoch 1: 15%|█▍ | 274/1875 [00:04<00:29, 54.97it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 15%|█▍ | 275/1875 [00:05<00:29, 54.97it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 15%|█▍ | 275/1875 [00:05<00:29, 54.97it/s, v_num=13, train_loss=0.260, Acc%=96.40]
Epoch 1: 15%|█▍ | 276/1875 [00:05<00:29, 54.97it/s, v_num=13, train_loss=0.260, Acc%=96.40]
Epoch 1: 15%|█▍ | 276/1875 [00:05<00:29, 54.97it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 15%|█▍ | 277/1875 [00:05<00:29, 54.96it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 15%|█▍ | 277/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.524, Acc%=96.40]
Epoch 1: 15%|█▍ | 278/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.524, Acc%=96.40]
Epoch 1: 15%|█▍ | 278/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.297, Acc%=96.40]
Epoch 1: 15%|█▍ | 279/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.297, Acc%=96.40]
Epoch 1: 15%|█▍ | 279/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.450, Acc%=96.40]
Epoch 1: 15%|█▍ | 280/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.450, Acc%=96.40]
Epoch 1: 15%|█▍ | 280/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.154, Acc%=96.40]
Epoch 1: 15%|█▍ | 281/1875 [00:05<00:29, 54.95it/s, v_num=13, train_loss=0.154, Acc%=96.40]
Epoch 1: 15%|█▍ | 281/1875 [00:05<00:29, 54.94it/s, v_num=13, train_loss=0.308, Acc%=96.40]
Epoch 1: 15%|█▌ | 282/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.308, Acc%=96.40]
Epoch 1: 15%|█▌ | 282/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.221, Acc%=96.40]
Epoch 1: 15%|█▌ | 283/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.221, Acc%=96.40]
Epoch 1: 15%|█▌ | 283/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 15%|█▌ | 284/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 15%|█▌ | 284/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.716, Acc%=96.40]
Epoch 1: 15%|█▌ | 285/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.716, Acc%=96.40]
Epoch 1: 15%|█▌ | 285/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 15%|█▌ | 286/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 15%|█▌ | 286/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.0913, Acc%=96.40]
Epoch 1: 15%|█▌ | 287/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.0913, Acc%=96.40]
Epoch 1: 15%|█▌ | 287/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.321, Acc%=96.40]
Epoch 1: 15%|█▌ | 288/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.321, Acc%=96.40]
Epoch 1: 15%|█▌ | 288/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.184, Acc%=96.40]
Epoch 1: 15%|█▌ | 289/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.184, Acc%=96.40]
Epoch 1: 15%|█▌ | 289/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 15%|█▌ | 290/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 15%|█▌ | 290/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.121, Acc%=96.40]
Epoch 1: 16%|█▌ | 291/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.121, Acc%=96.40]
Epoch 1: 16%|█▌ | 291/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.125, Acc%=96.40]
Epoch 1: 16%|█▌ | 292/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.125, Acc%=96.40]
Epoch 1: 16%|█▌ | 292/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 16%|█▌ | 293/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 16%|█▌ | 293/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.186, Acc%=96.40]
Epoch 1: 16%|█▌ | 294/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.186, Acc%=96.40]
Epoch 1: 16%|█▌ | 294/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 16%|█▌ | 295/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 16%|█▌ | 295/1875 [00:05<00:28, 54.92it/s, v_num=13, train_loss=0.451, Acc%=96.40]
Epoch 1: 16%|█▌ | 296/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.451, Acc%=96.40]
Epoch 1: 16%|█▌ | 296/1875 [00:05<00:28, 54.92it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 16%|█▌ | 297/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 16%|█▌ | 297/1875 [00:05<00:28, 54.92it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 16%|█▌ | 298/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 16%|█▌ | 298/1875 [00:05<00:28, 54.92it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 16%|█▌ | 299/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 16%|█▌ | 299/1875 [00:05<00:28, 54.92it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 16%|█▌ | 300/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 16%|█▌ | 300/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.260, Acc%=96.40]
Epoch 1: 16%|█▌ | 301/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.260, Acc%=96.40]
Epoch 1: 16%|█▌ | 301/1875 [00:05<00:28, 54.93it/s, v_num=13, train_loss=0.569, Acc%=96.40]
Epoch 1: 16%|█▌ | 302/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.569, Acc%=96.40]
Epoch 1: 16%|█▌ | 302/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 16%|█▌ | 303/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 16%|█▌ | 303/1875 [00:05<00:28, 54.94it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 16%|█▌ | 304/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 16%|█▌ | 304/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 16%|█▋ | 305/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 16%|█▋ | 305/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 16%|█▋ | 306/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 16%|█▋ | 306/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.0883, Acc%=96.40]
Epoch 1: 16%|█▋ | 307/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.0883, Acc%=96.40]
Epoch 1: 16%|█▋ | 307/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 16%|█▋ | 308/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 16%|█▋ | 308/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 16%|█▋ | 309/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 16%|█▋ | 309/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.421, Acc%=96.40]
Epoch 1: 17%|█▋ | 310/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.421, Acc%=96.40]
Epoch 1: 17%|█▋ | 310/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 17%|█▋ | 311/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 17%|█▋ | 311/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.0706, Acc%=96.40]
Epoch 1: 17%|█▋ | 312/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.0706, Acc%=96.40]
Epoch 1: 17%|█▋ | 312/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 17%|█▋ | 313/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 17%|█▋ | 313/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.383, Acc%=96.40]
Epoch 1: 17%|█▋ | 314/1875 [00:05<00:28, 54.97it/s, v_num=13, train_loss=0.383, Acc%=96.40]
Epoch 1: 17%|█▋ | 314/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.118, Acc%=96.40]
Epoch 1: 17%|█▋ | 315/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.118, Acc%=96.40]
Epoch 1: 17%|█▋ | 315/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.0972, Acc%=96.40]
Epoch 1: 17%|█▋ | 316/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.0972, Acc%=96.40]
Epoch 1: 17%|█▋ | 316/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.208, Acc%=96.40]
Epoch 1: 17%|█▋ | 317/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.208, Acc%=96.40]
Epoch 1: 17%|█▋ | 317/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 17%|█▋ | 318/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 17%|█▋ | 318/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 17%|█▋ | 319/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 17%|█▋ | 319/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.291, Acc%=96.40]
Epoch 1: 17%|█▋ | 320/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.291, Acc%=96.40]
Epoch 1: 17%|█▋ | 320/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 17%|█▋ | 321/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 17%|█▋ | 321/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.272, Acc%=96.40]
Epoch 1: 17%|█▋ | 322/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.272, Acc%=96.40]
Epoch 1: 17%|█▋ | 322/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 17%|█▋ | 323/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 17%|█▋ | 323/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.441, Acc%=96.40]
Epoch 1: 17%|█▋ | 324/1875 [00:05<00:28, 54.96it/s, v_num=13, train_loss=0.441, Acc%=96.40]
Epoch 1: 17%|█▋ | 324/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.174, Acc%=96.40]
Epoch 1: 17%|█▋ | 325/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.174, Acc%=96.40]
Epoch 1: 17%|█▋ | 325/1875 [00:05<00:28, 54.95it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 17%|█▋ | 326/1875 [00:05<00:28, 54.88it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 17%|█▋ | 326/1875 [00:05<00:28, 54.88it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 17%|█▋ | 327/1875 [00:05<00:28, 54.88it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 17%|█▋ | 327/1875 [00:05<00:28, 54.87it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 17%|█▋ | 328/1875 [00:05<00:28, 54.87it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 17%|█▋ | 328/1875 [00:05<00:28, 54.87it/s, v_num=13, train_loss=0.272, Acc%=96.40]
Epoch 1: 18%|█▊ | 329/1875 [00:05<00:28, 54.87it/s, v_num=13, train_loss=0.272, Acc%=96.40]
Epoch 1: 18%|█▊ | 329/1875 [00:05<00:28, 54.86it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 18%|█▊ | 330/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 18%|█▊ | 330/1875 [00:06<00:28, 54.86it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 18%|█▊ | 331/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 18%|█▊ | 331/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 18%|█▊ | 332/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 18%|█▊ | 332/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.128, Acc%=96.40]
Epoch 1: 18%|█▊ | 333/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.128, Acc%=96.40]
Epoch 1: 18%|█▊ | 333/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.0677, Acc%=96.40]
Epoch 1: 18%|█▊ | 334/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.0677, Acc%=96.40]
Epoch 1: 18%|█▊ | 334/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.455, Acc%=96.40]
Epoch 1: 18%|█▊ | 335/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.455, Acc%=96.40]
Epoch 1: 18%|█▊ | 335/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 18%|█▊ | 336/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.287, Acc%=96.40]
Epoch 1: 18%|█▊ | 336/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.475, Acc%=96.40]
Epoch 1: 18%|█▊ | 337/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.475, Acc%=96.40]
Epoch 1: 18%|█▊ | 337/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 18%|█▊ | 338/1875 [00:06<00:28, 54.88it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 18%|█▊ | 338/1875 [00:06<00:28, 54.87it/s, v_num=13, train_loss=0.261, Acc%=96.40]
Epoch 1: 18%|█▊ | 339/1875 [00:06<00:27, 54.88it/s, v_num=13, train_loss=0.261, Acc%=96.40]
Epoch 1: 18%|█▊ | 339/1875 [00:06<00:27, 54.88it/s, v_num=13, train_loss=0.617, Acc%=96.40]
Epoch 1: 18%|█▊ | 340/1875 [00:06<00:27, 54.88it/s, v_num=13, train_loss=0.617, Acc%=96.40]
Epoch 1: 18%|█▊ | 340/1875 [00:06<00:27, 54.88it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 18%|█▊ | 341/1875 [00:06<00:27, 54.89it/s, v_num=13, train_loss=0.241, Acc%=96.40]
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Epoch 1: 18%|█▊ | 342/1875 [00:06<00:27, 54.89it/s, v_num=13, train_loss=0.441, Acc%=96.40]
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Epoch 1: 54%|█████▍ | 1012/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.0828, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1012/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.0821, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1013/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.0821, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1013/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1014/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1014/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.397, Acc%=96.40]
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Epoch 1: 54%|█████▍ | 1015/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.0774, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1016/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.0774, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1016/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1017/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1017/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.289, Acc%=96.40]
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Epoch 1: 54%|█████▍ | 1018/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.275, Acc%=96.40]
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Epoch 1: 54%|█████▍ | 1019/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1020/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1020/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.177, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1021/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.177, Acc%=96.40]
Epoch 1: 54%|█████▍ | 1021/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1022/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1022/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.0665, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1023/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.240, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1024/1875 [00:18<00:15, 55.06it/s, v_num=13, train_loss=0.240, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1024/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.536, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1025/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.129, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1026/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.338, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1027/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.408, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1028/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.408, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1028/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.350, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1029/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.350, Acc%=96.40]
Epoch 1: 55%|█████▍ | 1029/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.285, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1030/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.182, Acc%=96.40]
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Epoch 1: 55%|█████▍ | 1031/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1032/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1032/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1033/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1033/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.149, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1034/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.149, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1034/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1035/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1035/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.348, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1036/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.348, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1036/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.109, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1037/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.109, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1037/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.413, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1038/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.413, Acc%=96.40]
Epoch 1: 55%|█████▌ | 1038/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.260, Acc%=96.40]
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Epoch 1: 55%|█████▌ | 1039/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.283, Acc%=96.40]
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Epoch 1: 55%|█████▌ | 1040/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.261, Acc%=96.40]
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Epoch 1: 56%|█████▌ | 1041/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.222, Acc%=96.40]
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Epoch 1: 56%|█████▌ | 1042/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.205, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1043/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.205, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1043/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1044/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1044/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.127, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1045/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.127, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1045/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.323, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1046/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.323, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1046/1875 [00:18<00:15, 55.05it/s, v_num=13, train_loss=0.157, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1047/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.157, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1047/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1048/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1048/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.367, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1049/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.367, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1049/1875 [00:19<00:15, 55.05it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1050/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1050/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.348, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1051/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.348, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1051/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.120, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1052/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.120, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1052/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.0812, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1053/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.0812, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1053/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1054/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 56%|█████▌ | 1054/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1055/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1055/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.386, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1056/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.386, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1056/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1057/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1057/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.0919, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1058/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.0919, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1058/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.486, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1059/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.486, Acc%=96.40]
Epoch 1: 56%|█████▋ | 1059/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.234, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1060/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.234, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1060/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1061/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1061/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1062/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1062/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1063/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1063/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.230, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1064/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.230, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1064/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1065/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1065/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.305, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1066/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.305, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1066/1875 [00:19<00:14, 55.04it/s, v_num=13, train_loss=0.0625, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1067/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.0625, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1067/1875 [00:19<00:14, 55.04it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1068/1875 [00:19<00:14, 55.05it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1068/1875 [00:19<00:14, 55.04it/s, v_num=13, train_loss=0.171, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1069/1875 [00:19<00:14, 55.04it/s, v_num=13, train_loss=0.171, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1069/1875 [00:19<00:14, 55.04it/s, v_num=13, train_loss=0.236, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1070/1875 [00:19<00:14, 55.03it/s, v_num=13, train_loss=0.236, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1070/1875 [00:19<00:14, 55.03it/s, v_num=13, train_loss=0.310, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1071/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.210, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1072/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.210, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1072/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.139, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1073/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.261, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1074/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.267, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1075/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.374, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1076/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.242, Acc%=96.40]
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Epoch 1: 57%|█████▋ | 1077/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1078/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 57%|█████▋ | 1078/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.153, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1079/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.153, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1079/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1080/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1080/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1081/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1081/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1082/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1082/1875 [00:19<00:14, 55.01it/s, v_num=13, train_loss=0.402, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1083/1875 [00:19<00:14, 54.99it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1084/1875 [00:19<00:14, 54.97it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1084/1875 [00:19<00:14, 54.97it/s, v_num=13, train_loss=0.321, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1086/1875 [00:19<00:14, 54.96it/s, v_num=13, train_loss=0.146, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1087/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.189, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1088/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.253, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1089/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.0594, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1090/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.226, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1091/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.194, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1092/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.278, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1093/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.142, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1094/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.198, Acc%=96.40]
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Epoch 1: 58%|█████▊ | 1095/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.118, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1096/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.118, Acc%=96.40]
Epoch 1: 58%|█████▊ | 1096/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.0754, Acc%=96.40]
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Epoch 1: 59%|█████▊ | 1097/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.191, Acc%=96.40]
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Epoch 1: 59%|█████▊ | 1098/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.265, Acc%=96.40]
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Epoch 1: 59%|█████▊ | 1099/1875 [00:19<00:14, 54.95it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 59%|█████▊ | 1100/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 59%|█████▊ | 1100/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.101, Acc%=96.40]
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Epoch 1: 59%|█████▊ | 1101/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.141, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1102/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.150, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1103/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.0957, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1104/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.297, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1105/1875 [00:20<00:14, 54.95it/s, v_num=13, train_loss=0.0663, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1106/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.0663, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1106/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1107/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1107/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.163, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1108/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.163, Acc%=96.40]
Epoch 1: 59%|█████▉ | 1108/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.181, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1109/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.0827, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1110/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.091, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1113/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.319, Acc%=96.40]
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Epoch 1: 59%|█████▉ | 1115/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.271, Acc%=96.40]
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Epoch 1: 60%|█████▉ | 1116/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1117/1875 [00:20<00:13, 54.95it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1117/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.207, Acc%=96.40]
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Epoch 1: 60%|█████▉ | 1118/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.357, Acc%=96.40]
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Epoch 1: 60%|█████▉ | 1119/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.589, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1120/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.589, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1120/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.458, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1121/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.458, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1121/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0588, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1122/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0588, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1122/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.102, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1123/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.102, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1123/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.143, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1124/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.143, Acc%=96.40]
Epoch 1: 60%|█████▉ | 1124/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.223, Acc%=96.40]
Epoch 1: 60%|██████ | 1125/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.223, Acc%=96.40]
Epoch 1: 60%|██████ | 1125/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.206, Acc%=96.40]
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Epoch 1: 60%|██████ | 1126/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 60%|██████ | 1127/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 60%|██████ | 1127/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 60%|██████ | 1128/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 60%|██████ | 1128/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.548, Acc%=96.40]
Epoch 1: 60%|██████ | 1129/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.548, Acc%=96.40]
Epoch 1: 60%|██████ | 1129/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 60%|██████ | 1130/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 60%|██████ | 1130/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.115, Acc%=96.40]
Epoch 1: 60%|██████ | 1131/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.115, Acc%=96.40]
Epoch 1: 60%|██████ | 1131/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.440, Acc%=96.40]
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Epoch 1: 60%|██████ | 1132/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.236, Acc%=96.40]
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Epoch 1: 60%|██████ | 1133/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.287, Acc%=96.40]
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Epoch 1: 60%|██████ | 1134/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.128, Acc%=96.40]
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Epoch 1: 61%|██████ | 1135/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.182, Acc%=96.40]
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Epoch 1: 61%|██████ | 1136/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0497, Acc%=96.40]
Epoch 1: 61%|██████ | 1137/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0497, Acc%=96.40]
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Epoch 1: 61%|██████ | 1138/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0984, Acc%=96.40]
Epoch 1: 61%|██████ | 1139/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0984, Acc%=96.40]
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Epoch 1: 61%|██████ | 1140/1875 [00:20<00:13, 54.94it/s, v_num=13, train_loss=0.0664, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1157/1875 [00:21<00:13, 54.94it/s, v_num=13, train_loss=0.211, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1158/1875 [00:21<00:13, 54.94it/s, v_num=13, train_loss=0.246, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1160/1875 [00:21<00:13, 54.94it/s, v_num=13, train_loss=0.198, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1163/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.183, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1164/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.188, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1166/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.182, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1167/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.123, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1168/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.332, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1169/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.414, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1170/1875 [00:21<00:12, 54.93it/s, v_num=13, train_loss=0.333, Acc%=96.40]
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Epoch 1: 62%|██████▏ | 1171/1875 [00:21<00:12, 54.93it/s, v_num=13, train_loss=0.246, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1172/1875 [00:21<00:12, 54.93it/s, v_num=13, train_loss=0.218, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1173/1875 [00:21<00:12, 54.93it/s, v_num=13, train_loss=0.369, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1180/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 63%|██████▎ | 1181/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 63%|██████▎ | 1181/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.255, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1182/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.231, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1185/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.128, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1187/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.332, Acc%=96.40]
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Epoch 1: 63%|██████▎ | 1190/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.279, Acc%=96.40]
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Epoch 1: 64%|██████▎ | 1191/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.149, Acc%=96.40]
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Epoch 1: 64%|██████▎ | 1192/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.316, Acc%=96.40]
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Epoch 1: 64%|██████▎ | 1193/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.226, Acc%=96.40]
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Epoch 1: 64%|██████▎ | 1194/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.332, Acc%=96.40]
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Epoch 1: 64%|██████▎ | 1195/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.129, Acc%=96.40]
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Epoch 1: 64%|██████▍ | 1196/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.114, Acc%=96.40]
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Epoch 1: 64%|██████▍ | 1197/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.238, Acc%=96.40]
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Epoch 1: 64%|██████▍ | 1198/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.281, Acc%=96.40]
Epoch 1: 64%|██████▍ | 1199/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.281, Acc%=96.40]
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Epoch 1: 64%|██████▍ | 1200/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.224, Acc%=96.40]
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Epoch 1: 64%|██████▍ | 1202/1875 [00:21<00:12, 54.94it/s, v_num=13, train_loss=0.253, Acc%=96.40]
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Epoch 1: 71%|███████ | 1322/1875 [00:24<00:10, 54.97it/s, v_num=13, train_loss=0.396, Acc%=96.40]
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Epoch 1: 71%|███████ | 1323/1875 [00:24<00:10, 54.97it/s, v_num=13, train_loss=0.196, Acc%=96.40]
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Epoch 1: 71%|███████▏ | 1336/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.441, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1336/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1337/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1337/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.244, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1338/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.244, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1338/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.333, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1339/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.333, Acc%=96.40]
Epoch 1: 71%|███████▏ | 1339/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.189, Acc%=96.40]
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Epoch 1: 71%|███████▏ | 1340/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.0561, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1342/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.221, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1343/1875 [00:24<00:09, 54.97it/s, v_num=13, train_loss=0.186, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1345/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.248, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1346/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.314, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1347/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.211, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1348/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.284, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1349/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.442, Acc%=96.40]
Epoch 1: 72%|███████▏ | 1350/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.442, Acc%=96.40]
Epoch 1: 72%|███████▏ | 1350/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.160, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1351/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.229, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1352/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.307, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1353/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.157, Acc%=96.40]
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Epoch 1: 72%|███████▏ | 1355/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.255, Acc%=96.40]
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Epoch 1: 73%|███████▎ | 1371/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.446, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1372/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.446, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1372/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1373/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1373/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1374/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.252, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1374/1875 [00:24<00:09, 54.98it/s, v_num=13, train_loss=0.137, Acc%=96.40]
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Epoch 1: 73%|███████▎ | 1375/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.318, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1376/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.318, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1376/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.243, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1377/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.243, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1377/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.527, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1378/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.527, Acc%=96.40]
Epoch 1: 73%|███████▎ | 1378/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.243, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1379/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.243, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1379/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1380/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.335, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1380/1875 [00:25<00:09, 54.98it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1381/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1381/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1382/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 74%|███████▎ | 1382/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1383/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1383/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0626, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1384/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0626, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1384/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.342, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1385/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.342, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1385/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1386/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1386/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1387/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1387/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1388/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1388/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0982, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1389/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0982, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1389/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.302, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1390/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.302, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1390/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1391/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1391/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1392/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1392/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1393/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1393/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0918, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1394/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.0918, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1394/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.144, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1395/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.144, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1395/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.135, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1396/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.135, Acc%=96.40]
Epoch 1: 74%|███████▍ | 1396/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.363, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1397/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.363, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1397/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.320, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1398/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.320, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1398/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1399/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1399/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.257, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1400/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.257, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1400/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1401/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1401/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.284, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1402/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.284, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1402/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.185, Acc%=96.40]
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Epoch 1: 75%|███████▍ | 1403/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1404/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1404/1875 [00:25<00:08, 54.97it/s, v_num=13, train_loss=0.326, Acc%=96.40]
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Epoch 1: 75%|███████▍ | 1405/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1406/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 75%|███████▍ | 1406/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0917, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1407/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.0917, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1407/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.283, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1408/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.283, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1408/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1409/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1409/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1410/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1410/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.289, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1411/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.289, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1411/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1412/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1412/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1413/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1413/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1414/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.164, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1414/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1415/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.226, Acc%=96.40]
Epoch 1: 75%|███████▌ | 1415/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1416/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1416/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.114, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1417/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.114, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1417/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.193, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1418/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.193, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1418/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.222, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1419/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.222, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1419/1875 [00:25<00:08, 54.98it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1420/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1420/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1421/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1421/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.0667, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1422/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.0667, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1422/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1423/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.375, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1423/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1424/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1424/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.0392, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1425/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.0392, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1425/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.217, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1426/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.217, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1426/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1427/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.312, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1427/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1428/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1428/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1429/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 76%|███████▌ | 1429/1875 [00:25<00:08, 54.99it/s, v_num=13, train_loss=0.170, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1430/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.170, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1430/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1431/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1431/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.481, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1432/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.481, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1432/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.0753, Acc%=96.40]
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Epoch 1: 76%|███████▋ | 1433/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1434/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 76%|███████▋ | 1434/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1435/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1435/1875 [00:26<00:08, 54.99it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1436/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1436/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.150, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1437/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.150, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1437/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.329, Acc%=96.40]
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Epoch 1: 77%|███████▋ | 1438/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.205, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1439/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.205, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1439/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.150, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1440/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.150, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1440/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1441/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1441/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.256, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1442/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.256, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1442/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.286, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1443/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.286, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1443/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1444/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.198, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1444/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1445/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1445/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.120, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1446/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.120, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1446/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1447/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1447/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1448/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.275, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1448/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.114, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1449/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.114, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1449/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.119, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1450/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.119, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1450/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1451/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1451/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.0916, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1452/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.0916, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1452/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1453/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 77%|███████▋ | 1453/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.0849, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1454/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.0849, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1454/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.220, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1455/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.220, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1455/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1456/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1456/1875 [00:26<00:07, 54.99it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1457/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1457/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.119, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1458/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.119, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1458/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.383, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1459/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.383, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1459/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1460/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1460/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1461/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1461/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1462/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1462/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1463/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1463/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1464/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.165, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1464/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.365, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1465/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.365, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1465/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.416, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1466/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.416, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1466/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1467/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1467/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1468/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1468/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.364, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1469/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.364, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1469/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1470/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1470/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1471/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 78%|███████▊ | 1471/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.403, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1472/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.403, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1472/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1473/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1473/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1474/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1474/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1475/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1475/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.422, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1476/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.422, Acc%=96.40]
Epoch 1: 79%|███████▊ | 1476/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1477/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.360, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1477/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1478/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.337, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1478/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.334, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1479/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.334, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1479/1875 [00:26<00:07, 55.00it/s, v_num=13, train_loss=0.0512, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1480/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.0512, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1480/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1481/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1481/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.178, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1482/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.178, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1482/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.106, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1483/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.106, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1483/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1484/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1484/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.100, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1485/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.100, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1485/1875 [00:26<00:07, 55.01it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1486/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1486/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.161, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1487/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.161, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1487/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.219, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1488/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.219, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1488/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.193, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1489/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.193, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1489/1875 [00:27<00:07, 55.01it/s, v_num=13, train_loss=0.123, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1490/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.123, Acc%=96.40]
Epoch 1: 79%|███████▉ | 1490/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1491/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1491/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.225, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1492/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.225, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1492/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1493/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1493/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1494/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1494/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1495/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1495/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.143, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1496/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.143, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1496/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1497/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.338, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1497/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1498/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1498/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.459, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1499/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.459, Acc%=96.40]
Epoch 1: 80%|███████▉ | 1499/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.371, Acc%=96.40]
Epoch 1: 80%|████████ | 1500/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.371, Acc%=96.40]
Epoch 1: 80%|████████ | 1500/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 80%|████████ | 1501/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.354, Acc%=96.40]
Epoch 1: 80%|████████ | 1501/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 80%|████████ | 1502/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 80%|████████ | 1502/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 80%|████████ | 1503/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 80%|████████ | 1503/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 80%|████████ | 1504/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.160, Acc%=96.40]
Epoch 1: 80%|████████ | 1504/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 80%|████████ | 1505/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.185, Acc%=96.40]
Epoch 1: 80%|████████ | 1505/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.0674, Acc%=96.40]
Epoch 1: 80%|████████ | 1506/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.0674, Acc%=96.40]
Epoch 1: 80%|████████ | 1506/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 80%|████████ | 1507/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.179, Acc%=96.40]
Epoch 1: 80%|████████ | 1507/1875 [00:27<00:06, 55.00it/s, v_num=13, train_loss=0.430, Acc%=96.40]
Epoch 1: 80%|████████ | 1508/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.430, Acc%=96.40]
Epoch 1: 80%|████████ | 1508/1875 [00:27<00:06, 55.00it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 80%|████████ | 1509/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 80%|████████ | 1509/1875 [00:27<00:06, 55.00it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 81%|████████ | 1510/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 81%|████████ | 1510/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 81%|████████ | 1511/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.112, Acc%=96.40]
Epoch 1: 81%|████████ | 1511/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.145, Acc%=96.40]
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Epoch 1: 81%|████████ | 1512/1875 [00:27<00:06, 55.01it/s, v_num=13, train_loss=0.0754, Acc%=96.40]
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Epoch 1: 83%|████████▎ | 1548/1875 [00:28<00:05, 55.01it/s, v_num=13, train_loss=0.144, Acc%=96.40]
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Epoch 1: 83%|████████▎ | 1550/1875 [00:28<00:05, 55.01it/s, v_num=13, train_loss=0.127, Acc%=96.40]
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Epoch 1: 84%|████████▍ | 1584/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.286, Acc%=96.40]
Epoch 1: 84%|████████▍ | 1584/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1585/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1585/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.443, Acc%=96.40]
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Epoch 1: 85%|████████▍ | 1586/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1587/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.209, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1587/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.349, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1588/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.349, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1588/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1589/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1589/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1590/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.292, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1590/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1591/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.264, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1591/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1592/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1592/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1593/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 85%|████████▍ | 1593/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.0704, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1594/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.0704, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1594/1875 [00:28<00:05, 54.97it/s, v_num=13, train_loss=0.250, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1595/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.250, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1595/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.351, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1596/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.351, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1596/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1597/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1597/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1598/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.309, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1598/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1599/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1599/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.247, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1600/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.247, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1600/1875 [00:29<00:05, 54.97it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1601/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 85%|████████▌ | 1601/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.328, Acc%=96.40]
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Epoch 1: 85%|████████▌ | 1602/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.233, Acc%=96.40]
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Epoch 1: 85%|████████▌ | 1603/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.142, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1604/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.0783, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1605/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.119, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1606/1875 [00:29<00:04, 54.97it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1607/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1607/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0909, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1608/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0909, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1608/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0577, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1609/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0577, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1609/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.512, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1610/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.512, Acc%=96.40]
Epoch 1: 86%|████████▌ | 1610/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.368, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1611/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.267, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1613/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0782, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1614/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.146, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1615/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.254, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1616/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.345, Acc%=96.40]
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Epoch 1: 86%|████████▌ | 1617/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.0936, Acc%=96.40]
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Epoch 1: 86%|████████▋ | 1618/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1619/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1619/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1620/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1620/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1621/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 86%|████████▋ | 1621/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1622/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.175, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1622/1875 [00:29<00:04, 54.98it/s, v_num=13, train_loss=0.155, Acc%=96.40]
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Epoch 1: 87%|████████▋ | 1623/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.262, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1624/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.262, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1624/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.457, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1625/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.457, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1625/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.265, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1626/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.265, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1626/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0717, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1627/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0717, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1627/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1628/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1628/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1629/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1629/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0825, Acc%=96.40]
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Epoch 1: 87%|████████▋ | 1630/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0978, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1631/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0978, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1631/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0847, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1632/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0847, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1632/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.365, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1633/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.365, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1633/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1634/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1634/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1635/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1635/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.273, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1636/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.273, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1636/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1637/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.110, Acc%=96.40]
Epoch 1: 87%|████████▋ | 1637/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.264, Acc%=96.40]
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Epoch 1: 87%|████████▋ | 1638/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.236, Acc%=96.40]
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Epoch 1: 87%|████████▋ | 1639/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.313, Acc%=96.40]
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Epoch 1: 87%|████████▋ | 1640/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.341, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1641/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.341, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1641/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.214, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1642/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.214, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1642/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.232, Acc%=96.40]
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Epoch 1: 88%|████████▊ | 1643/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.304, Acc%=96.40]
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Epoch 1: 88%|████████▊ | 1644/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.0726, Acc%=96.40]
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Epoch 1: 88%|████████▊ | 1645/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1646/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.159, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1646/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.298, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1647/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.298, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1647/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1648/1875 [00:29<00:04, 55.00it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1648/1875 [00:29<00:04, 54.99it/s, v_num=13, train_loss=0.277, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1649/1875 [00:29<00:04, 55.00it/s, v_num=13, train_loss=0.277, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1649/1875 [00:29<00:04, 55.00it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1650/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1650/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1651/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1651/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.102, Acc%=96.40]
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Epoch 1: 88%|████████▊ | 1652/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.0738, Acc%=96.40]
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Epoch 1: 88%|████████▊ | 1653/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1654/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.258, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1654/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1655/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1655/1875 [00:30<00:04, 55.00it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1656/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1656/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1657/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1657/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.418, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1658/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.418, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1658/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.403, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1659/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.403, Acc%=96.40]
Epoch 1: 88%|████████▊ | 1659/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.0591, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1660/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.0591, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1660/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.576, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1661/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.576, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1661/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1662/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.216, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1662/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.345, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1663/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.345, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1663/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1664/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 89%|████████▊ | 1664/1875 [00:30<00:03, 55.00it/s, v_num=13, train_loss=0.169, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1665/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.169, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1665/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.161, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1666/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.161, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1666/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.232, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1667/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.232, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1667/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.0714, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1668/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.0714, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1668/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1669/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1669/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.0781, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1670/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.0781, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1670/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1671/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.195, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1671/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1672/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.267, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1672/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1673/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.158, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1673/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1674/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.254, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1674/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.152, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1675/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.152, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1675/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.104, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1676/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.104, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1676/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.204, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1677/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.204, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1677/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1678/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.373, Acc%=96.40]
Epoch 1: 89%|████████▉ | 1678/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.357, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1679/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.357, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1679/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1680/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1680/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.382, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1681/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.382, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1681/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.214, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1682/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.214, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1682/1875 [00:30<00:03, 55.01it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1683/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.141, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1683/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.673, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1684/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.673, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1684/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1685/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1685/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.362, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1686/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.362, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1686/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.0708, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1687/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.0708, Acc%=96.40]
Epoch 1: 90%|████████▉ | 1687/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 90%|█████████ | 1688/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.237, Acc%=96.40]
Epoch 1: 90%|█████████ | 1688/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 90%|█████████ | 1689/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.242, Acc%=96.40]
Epoch 1: 90%|█████████ | 1689/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.131, Acc%=96.40]
Epoch 1: 90%|█████████ | 1690/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.131, Acc%=96.40]
Epoch 1: 90%|█████████ | 1690/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 90%|█████████ | 1691/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.201, Acc%=96.40]
Epoch 1: 90%|█████████ | 1691/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.0934, Acc%=96.40]
Epoch 1: 90%|█████████ | 1692/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.0934, Acc%=96.40]
Epoch 1: 90%|█████████ | 1692/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 90%|█████████ | 1693/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 90%|█████████ | 1693/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.104, Acc%=96.40]
Epoch 1: 90%|█████████ | 1694/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.104, Acc%=96.40]
Epoch 1: 90%|█████████ | 1694/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 90%|█████████ | 1695/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 90%|█████████ | 1695/1875 [00:30<00:03, 55.02it/s, v_num=13, train_loss=0.135, Acc%=96.40]
Epoch 1: 90%|█████████ | 1696/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.135, Acc%=96.40]
Epoch 1: 90%|█████████ | 1696/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.200, Acc%=96.40]
Epoch 1: 91%|█████████ | 1697/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.200, Acc%=96.40]
Epoch 1: 91%|█████████ | 1697/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.234, Acc%=96.40]
Epoch 1: 91%|█████████ | 1698/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.234, Acc%=96.40]
Epoch 1: 91%|█████████ | 1698/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 91%|█████████ | 1699/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 91%|█████████ | 1699/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.197, Acc%=96.40]
Epoch 1: 91%|█████████ | 1700/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.197, Acc%=96.40]
Epoch 1: 91%|█████████ | 1700/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.464, Acc%=96.40]
Epoch 1: 91%|█████████ | 1701/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.464, Acc%=96.40]
Epoch 1: 91%|█████████ | 1701/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.372, Acc%=96.40]
Epoch 1: 91%|█████████ | 1702/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.372, Acc%=96.40]
Epoch 1: 91%|█████████ | 1702/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 91%|█████████ | 1703/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 91%|█████████ | 1703/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 91%|█████████ | 1704/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.224, Acc%=96.40]
Epoch 1: 91%|█████████ | 1704/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.0876, Acc%=96.40]
Epoch 1: 91%|█████████ | 1705/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.0876, Acc%=96.40]
Epoch 1: 91%|█████████ | 1705/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 91%|█████████ | 1706/1875 [00:30<00:03, 55.03it/s, v_num=13, train_loss=0.215, Acc%=96.40]
Epoch 1: 91%|█████████ | 1706/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 91%|█████████ | 1707/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 91%|█████████ | 1707/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 91%|█████████ | 1708/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 91%|█████████ | 1708/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.192, Acc%=96.40]
Epoch 1: 91%|█████████ | 1709/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.192, Acc%=96.40]
Epoch 1: 91%|█████████ | 1709/1875 [00:31<00:03, 55.03it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 91%|█████████ | 1710/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 91%|█████████ | 1710/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1711/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.183, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1711/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1712/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.133, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1712/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.0664, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1713/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.0664, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1713/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1714/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.315, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1714/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1715/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 91%|█████████▏| 1715/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.291, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1716/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.291, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1716/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1717/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.228, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1717/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.0602, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1718/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.0602, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1718/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.0914, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1719/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0914, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1719/1875 [00:31<00:02, 55.03it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1720/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1720/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1721/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.111, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1721/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1722/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1722/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1723/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.101, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1723/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1724/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.190, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1724/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0474, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1725/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0474, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1725/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.306, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1726/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.306, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1726/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1727/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1727/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0972, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1728/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0972, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1728/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1729/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.113, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1729/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1730/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.207, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1730/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1731/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.218, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1731/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1732/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.147, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1732/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1733/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1733/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1734/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.263, Acc%=96.40]
Epoch 1: 92%|█████████▏| 1734/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.567, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1735/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.567, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1735/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.171, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1736/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.171, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1736/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0956, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1737/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0956, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1737/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1738/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.191, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1738/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.136, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1739/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.136, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1739/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1740/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.203, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1740/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0674, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1741/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0674, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1741/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1742/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.280, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1742/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1743/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1743/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1744/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.293, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1744/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.130, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1745/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.130, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1745/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1746/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1746/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1747/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.166, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1747/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1748/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.140, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1748/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1749/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1749/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.152, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1750/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.152, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1750/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.240, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1751/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.240, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1751/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0526, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1752/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0526, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1752/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0778, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1753/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0778, Acc%=96.40]
Epoch 1: 93%|█████████▎| 1753/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.487, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1754/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.487, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1754/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1755/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1755/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0882, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1756/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0882, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1756/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.136, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1757/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.136, Acc%=96.40]
Epoch 1: 94%|█████████▎| 1757/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1758/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.251, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1758/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0959, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1759/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.0959, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1759/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1760/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1760/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.204, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1761/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.204, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1761/1875 [00:31<00:02, 55.04it/s, v_num=13, train_loss=0.407, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1762/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.407, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1762/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.0894, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1763/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.0894, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1763/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1764/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.155, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1764/1875 [00:32<00:02, 55.04it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1765/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.266, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1765/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1766/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.199, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1766/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.100, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1767/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.100, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1767/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.154, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1768/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.154, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1768/1875 [00:32<00:01, 55.04it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1769/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.148, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1769/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.410, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1770/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.410, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1770/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.331, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1771/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.331, Acc%=96.40]
Epoch 1: 94%|█████████▍| 1771/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.257, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1772/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.257, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1772/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.428, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1773/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.428, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1773/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.279, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1774/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.279, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1774/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1775/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1775/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.153, Acc%=96.40]
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Epoch 1: 95%|█████████▍| 1776/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1777/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.167, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1777/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.182, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1778/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.182, Acc%=96.40]
Epoch 1: 95%|█████████▍| 1778/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.134, Acc%=96.40]
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Epoch 1: 95%|█████████▍| 1779/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.162, Acc%=96.40]
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Epoch 1: 95%|█████████▍| 1780/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.134, Acc%=96.40]
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Epoch 1: 95%|█████████▍| 1781/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.0928, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1782/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.458, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1783/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.278, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1784/1875 [00:32<00:01, 55.05it/s, v_num=13, train_loss=0.254, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1786/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.493, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1789/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.123, Acc%=96.40]
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Epoch 1: 95%|█████████▌| 1790/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.241, Acc%=96.40]
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Epoch 1: 96%|█████████▌| 1791/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.126, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1792/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.126, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1792/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.0462, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1793/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.0462, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1793/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1794/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.211, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1794/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.142, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1795/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.142, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1795/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.137, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1796/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.137, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1796/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.117, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1797/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.117, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1797/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1798/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.300, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1798/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.105, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1799/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.105, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1799/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.109, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1800/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.109, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1800/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.040, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1801/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.040, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1801/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.0865, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1802/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.0865, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1802/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1803/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.103, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1803/1875 [00:32<00:01, 55.06it/s, v_num=13, train_loss=0.163, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1804/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.163, Acc%=96.40]
Epoch 1: 96%|█████████▌| 1804/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1805/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.213, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1805/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.301, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1806/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.301, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1806/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.246, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1807/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.246, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1807/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1808/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.212, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1808/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1809/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.278, Acc%=96.40]
Epoch 1: 96%|█████████▋| 1809/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1810/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1810/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.177, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1811/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.177, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1811/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.134, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1812/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.134, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1812/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.470, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1813/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.470, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1813/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.149, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1814/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.149, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1814/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1815/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.274, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1815/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.273, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1816/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.273, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1816/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1817/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1817/1875 [00:32<00:01, 55.07it/s, v_num=13, train_loss=0.491, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1818/1875 [00:33<00:01, 55.07it/s, v_num=13, train_loss=0.491, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1818/1875 [00:33<00:01, 55.07it/s, v_num=13, train_loss=0.462, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1819/1875 [00:33<00:01, 55.07it/s, v_num=13, train_loss=0.462, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1819/1875 [00:33<00:01, 55.07it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1820/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.238, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1820/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1821/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.173, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1821/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.446, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1822/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.446, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1822/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.298, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1823/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.298, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1823/1875 [00:33<00:00, 55.07it/s, v_num=13, train_loss=0.108, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1824/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.108, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1824/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1825/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.392, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1825/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1826/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.124, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1826/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1827/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.146, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1827/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1828/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.229, Acc%=96.40]
Epoch 1: 97%|█████████▋| 1828/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1829/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.343, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1829/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.117, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1830/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.117, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1830/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1831/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.347, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1831/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1832/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.233, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1832/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1833/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.366, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1833/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.607, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1834/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.607, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1834/1875 [00:33<00:00, 55.08it/s, v_num=13, train_loss=0.261, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1835/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.261, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1835/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0949, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1836/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0949, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1836/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.448, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1837/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.448, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1837/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1838/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.151, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1838/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0816, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1839/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0816, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1839/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1840/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.241, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1840/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1841/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.132, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1841/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.249, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1842/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.249, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1842/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1843/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.299, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1843/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0434, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1844/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0434, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1844/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0959, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1845/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.0959, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1845/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1846/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.187, Acc%=96.40]
Epoch 1: 98%|█████████▊| 1846/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.153, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1847/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.153, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1847/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1848/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.156, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1848/1875 [00:33<00:00, 55.09it/s, v_num=13, train_loss=0.529, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1849/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.529, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1849/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1850/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.129, Acc%=96.40]
Epoch 1: 99%|█████████▊| 1850/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.158, Acc%=96.40]
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Epoch 1: 99%|█████████▊| 1851/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1852/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.270, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1852/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1853/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.196, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1853/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.266, Acc%=96.40]
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Epoch 1: 99%|█████████▉| 1854/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.394, Acc%=96.40]
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Epoch 1: 99%|█████████▉| 1855/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.118, Acc%=96.40]
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Epoch 1: 99%|█████████▉| 1856/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.301, Acc%=96.40]
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Epoch 1: 99%|█████████▉| 1857/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.112, Acc%=96.40]
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Epoch 1: 99%|█████████▉| 1858/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.0901, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1859/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.0901, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1859/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.145, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1860/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.145, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1860/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1861/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.122, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1861/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.247, Acc%=96.40]
Epoch 1: 99%|█████████▉| 1862/1875 [00:33<00:00, 55.10it/s, v_num=13, train_loss=0.247, Acc%=96.40]
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┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Acc │ 97.780% │
│ Brier │ 0.04292 │
│ Entropy │ 0.20714 │
│ NLL │ 0.09973 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Calibration ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ ECE │ 0.04108 │
│ aECE │ 0.04098 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ OOD Detection ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUPR │ 95.214% │
│ AUROC │ 96.377% │
│ Entropy │ 1.30188 │
│ FPR95 │ 12.880% │
│ ens_Disagre… │ 0.60432 │
│ ens_Entropy │ 0.87732 │
│ ens_MI │ 0.42456 │
└──────────────┴───────────────────────────┘
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ Selective Classification ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ AUGRC │ 0.103% │
│ AURC │ 0.111% │
│ Cov@5Risk │ 100.000% │
│ Risk@80Cov │ 0.100% │
└──────────────┴───────────────────────────┘
The training time should be approximately similar to the one of the single model that you trained before. However, please note that we are working with very small models, hence completely underusing your GPU. As such, the training time is not representative of what you would observe with larger models.
You can read more on Packed-Ensembles in the paper or the Medium post.
To Go Further & More Concepts of Uncertainty in ML¶
Question 1: Have a look at the models in the “lightning_logs”. If you are on your own machine, try to visualize the learning curves with tensorboard –logdir lightning_logs.
Question 2: Add a cell below and try to find the errors made by packed-ensembles on the test set. Visualize the errors and their labels and look at the predictions of the different sub-models. Are they similar? Can you think of uncertainty scores that could help you identify these errors?
Selective Classification¶
Selective classification or “prediction with rejection” is a paradigm in uncertainty-aware machine learning where the model can decide not to make a prediction if the confidence score given by the model is below some pre-computed threshold. This can be useful in real-world applications where the cost of making a wrong prediction is high.
In constrast to calibration, the values of the confidence scores are not important, only the order of the scores. Ideally, the best model will order all the correct predictions first, and all the incorrect predictions last. In this case, there will be a threshold so that all the predictions above the threshold are correct, and all the predictions below the threshold are incorrect.
In TorchUncertainty, we look at 3 different metrics for selective classification: - AURC: The area under the Risk (% of errors) vs. Coverage (% of classified samples) curve. This curve expresses how the risk of the model evolves as we increase the coverage (the proportion of predictions that are above the selection threshold). This metric will be minimized by a model able to perfectly separate the correct and incorrect predictions.
The following metrics are computed at a fixed risk and coverage level and that have practical interests. The idea of these metrics is that you can set the selection threshold to achieve a certain level of risk and coverage, as required by the technical constraints of your application: - Coverage at 5% Risk: The proportion of predictions that are above the selection threshold when it is set for the risk to egal 5%. Set the risk threshold to your application constraints. The higher the better. - Risk at 80% Coverage: The proportion of errors when the coverage is set to 80%. Set the coverage threshold to your application constraints. The lower the better.
Grouping Loss¶
The grouping loss is a measure of uncertainty orthogonal to calibration. Have a look at this paper to learn about it. Check out their small library GLest. TorchUncertainty includes a wrapper of the library to compute the grouping loss with eval_grouping_loss parameter.
Total running time of the script: (3 minutes 28.824 seconds)