mxnet框架下超全手写字体识别—从数据预处理到网络的训练

Mxnet框架深度学习框架越来越受到大家的欢迎。但是如何正确的使用这一框架，很多人并不是很清楚。从训练数据的预处理，数据的生成（网络真正需要的数据格式，网络模型的保存，网络训练日志的保存，等等，虽然网上有很多的trick，但是大多数比较零散），这里，博主就从零开始，教大家训练手写字体（mnist）识别的一个完整的系统。

一、python、mxnet 如何安装。

trick：windows下使用pip安装Mxnet可能会错出，因为windows下的mxnet可能已来VC++2015或其他版本，linux下就不存在这种情况。

二、手写字体数据集如何获取。

import mxnet as mxmnist = mx.test_utils.get_mnist()  # 得到手写字体数据集

运行这行代码就可以下载到mnist数据集。mnist数据集主要包含四个压缩文件，截图如下：

说明：t10k-images-idx3-ubyte.gz：测试集图片二进制压缩文件

t10k-labels-idx1-ubyte.gz：测试集图片对应的标签二进制压缩文件

train-images-idx3-ubyte.gz：训练集图片二进制压缩文件

train-labels-idx1-ubyte.gz：训练集图片对应的标签二进制压缩文件

经常有人问我，为什么下载下来的图片打不开，根本不知道里面的图片长什么样子如何读取，如何进行训练，我只能说，这些图片已经被转成了2进制文件，并不是原始的图片。那么这些文件里面的图片到底是如何组织的呢？，通过下面的代码您就能完全了解。

由于我之前就已经下载过这4个压缩文件，所以直接从本地读取就可以了，没有必要重复下载，并且有时候并不能完全下载下来。

train_data_path = 'mnist_data/train-images-idx3-ubyte.gz'train_label_path = 'mnist_data/train-labels-idx1-ubyte.gz'test_data_path = 'mnist_data/t10k-images-idx3-ubyte.gz'test_label_path = 'mnist_data/t10k-labels-idx1-ubyte.gz'train_label, train_data = read_data(image_url=train_data_path, label_url=train_label_path)test_label, test_data = read_data(image_url=test_data_path, label_url=test_label_path)print('shape of train_data:', train_data.shape)print('shape of train_label:', train_label.shape)print('shape of test_data:', test_data.shape)print('shape of test_label:', test_label.shape)

输出结果：

shape of train_data: (60000, 1, 28, 28)shape of train_label: (60000,)shape of test_data: (10000, 1, 28, 28)shape of test_label: (10000,)

如果大家是初次下载，运行

mnist = mx.test_utils.get_mnist()

后就已经得到了一个完整的手写字体对象mnist。我们就可以直接通过下面的方式得到训练集以及测试的数据，代码如下：

train_image = mnist['train_data']train_image_label = mnist['train_label']test_image = mnist['test_data']testimage_label = mnist['test_label']

三、数据如何处理。

下载了mnist数据集，并且得到其具体的数据，该如何把这些数据转换成我们训练阶段真正需要的格式？从上面的print的信息中我们已经可以知道图片的大小已经是28×28、单通道灰度图。如果我们不对图片进行缩放的话，网络的输入应该是（batch_size, channel, height, width），所以我们需要把60000张训练集图片，10000张测试集图片转换成（60000//batch_size）×（batch_size, channel, height, width）、（10000//batch_size）×（batch_size, channel, height, width）的迭代的形式。

为什么mxnet里面的训练数据必须是以迭代器的形式传入的？1）简单，简单，简单！！！ 2）mxnet框架中，用户是不能像tensorflow框架那样写个for循环来显示的将数据送入到网络里面。那么如何正确的使用mxnet框架提供的迭代器呢？有的时候mxnet提供的迭代器类并不能满足所有的需求，我们还需要重写这个类。

熟悉mxnet框架的小伙伴，应该知道，mxnet框架中网络的输入主要包含两种：1）img，2）ndarray

一般来说，对于前者我们可以很方便的使用mxnet提供的img2rec.py这个文件，将所有的图片转换成rec文件，然后将这个rec文件作为网络的输入，其实也是一个迭代器对象。然而生成rec文件耗时，并且需要很大的额外空间，但是有没有一种办法不生成rec文件呢？当然有，就是上文提到的，重写DataIter类，返回一个迭代器对象，每一次迭代都是（batch_size, channel, height, width）的完整数据快，这样就可以将数据源源不断的送入到网络里面去。完整代码如下：

class Batch(object):    def __init__(self, data, label):        self.data = data        self.label = label

class Inter(mx.io.DataIter):    def __init__(self, batch_size, train_data, train_label):        super(Inter, self).__init__()        self.batch_size = batch_size        self.begin = 0        self.index = 0        self.train_data = train_data        self.train_label = train_label        self.train_count = len(train_data)        assert len(train_data) == len(train_label), 'Error'        assert (self.train_count >= self.batch_size) and (self.batch_size > 0), 'Error'        self.train_batches = self.train_count // self.batch_size    def __iter__(self):        return self    def reset(self):        self.begin = 0        self.index = 0    def next(self):        if self.iter_next():            return self.getdata()        else:            raise StopIteration    def __next__(self):        return self.next()    def iter_next(self):        if self.begin < self.train_batches:            return True        else:            return False    def get_batch_images_labels(self):        data = self.train_data[self.index:self.index + self.batch_size, :, :, :]        label = self.train_label[self.index:self.index + self.batch_size]        return data, label    def getdata(self):        images, labels = self.get_batch_images_labels()  # 顺序的得到数据        data_all = [mx.nd.array(images)]        label_all = [mx.nd.array(labels)]        self.index += self.batch_size        self.begin += 1        return Batch(data_all, label_all)    def getlabel(self):        pass    def getindex(self):        return None    def getpad(self):        pass

Inter这个类就简单的重写了原生的mxnet迭代器类DataIter。从我写的代码中就可以看出这个迭代器类每次都会返回一个Batch对象，数据（data）和标签（label），其中data的shape为：（batch_size, channel, height, width），label的shape为（batch_size,）请注意迭代器里面的reset方法。

四、神经网络的构建

mxnet框架里面有两个非常重要的包：symbol和gluon。我们完全可以通过这两个组件构建神经网络。当然也完全可以提通过ndarray对象构建神经网络。这里我会一一给出代码。

首先我给出网络上一张很经典的Lenet-5的网络结构图：

trick：有没有发现网络图片的原始输入是32×32，而我们的图片矩阵却是28×28的？所以我在具体实现的时候稍微调整了下网络结构。

1、使用symbol构建Lenet-5网络结构：

def get_net(class_num, bn_mom=0.99, filter_list=(6, 16)):    data = mx.sym.Variable('data')    imput = mx.sym.BatchNorm(data=data, fix_gamma=True, eps=1e-5, momentum=bn_mom, name='bn_imput')  # 批量标准化    # layer_1 卷积    layer_1 = mx.sym.Convolution(data=imput, num_filter=filter_list[0], kernel=(5, 5), stride=(2, 2), pad=(2, 2),                                 no_bias=False, name="conv_layer_1")    bn_layer_1 = mx.sym.BatchNorm(data=layer_1, fix_gamma=False, eps=1e-5, momentum=bn_mom, name='bn_layer_1')    a_bn_layer_1 = mx.sym.Activation(data=bn_layer_1, act_type='relu', name='relu_a_bn_layer_1')    # layer_2 卷积    bn_layer_2 = mx.sym.BatchNorm(data=a_bn_layer_1, fix_gamma=True, eps=1e-5, momentum=bn_mom, name='bn_layer_2')    conv_layer_2 = mx.sym.Convolution(data=bn_layer_2, num_filter=filter_list[1], kernel=(5, 5), stride=(1, 1),                                      pad=(0, 0), no_bias=False, name="conv_layer_2")    bn_layer_2_1 = mx.sym.BatchNorm(data=conv_layer_2, fix_gamma=False, eps=1e-5, momentum=bn_mom, name='bn_layer_2_1')    a_bn_layer_2 = mx.sym.Activation(data=bn_layer_2_1, act_type='relu', name='relu_a_a_bn_layer_2')    # 下采样层    pooling_layer_2 = mx.symbol.Pooling(data=a_bn_layer_2, kernel=(5, 5), stride=(2, 2), pad=(2, 2), pool_type='max',                                        name='pooling_layer_2')    # 全连接层    fc = mx.symbol.FullyConnected(data=pooling_layer_2, num_hidden=120, flatten=True, no_bias=False, name='fc')    bn1_fc = mx.sym.BatchNorm(data=fc, fix_gamma=False, eps=1e-5, momentum=bn_mom, name='bn1_fc')    fc1 = mx.symbol.FullyConnected(data=bn1_fc, num_hidden=84, flatten=True, no_bias=False, name='fc1')    bn1_fc1 = mx.sym.BatchNorm(data=fc1, fix_gamma=False, eps=1e-5, momentum=bn_mom, name='bn1_fc1')    fc2 = mx.symbol.FullyConnected(data=bn1_fc1, num_hidden=class_num, flatten=True, no_bias=False, name='fc2')    bn1_fc2 = mx.sym.BatchNorm(data=fc2, fix_gamma=False, eps=1e-5, momentum=bn_mom, name='bn1_fc2')    return mx.symbol.SoftmaxOutput(data=bn1_fc2, name='softmax')

2、使用gluon组件构建Lenet-5网络结构：

def create_net():    net = nn.Sequential()    with net.name_scope():         net.add(            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.Conv2D(channels=6, kernel_size=5, strides=2, padding=2, activation='relu'),            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.Conv2D(channels=16, kernel_size=5, strides=1, padding=0, activation='relu'),            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.AvgPool2D(pool_size=2, strides=2, padding=2),            nn.Flatten(),            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.Dense(120, activation='relu'),            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.Dense(84, activation='relu'),            nn.BatchNorm(epsilon=1e-5, momentum=0.9),            nn.Dense(10)        )    return net

3、使用mxnet的ndarray（区别于 numpy的 array）构建Lenet-5网络结构：

ctx = mx.cpu()  # 计算设备# 输出特征数目 = 6, 卷积核 = (5,5)----------第一个卷积层W1 = nd.random_normal(shape=(6, 1, 5, 5), scale=.1, ctx=ctx)b1 = nd.zeros(W1.shape[0], ctx=ctx)# 特征数目 = 16, 卷积核 = (5,5)----------第二个卷积层W2 = nd.random_normal(shape=(16, 6, 3, 3), scale=.1, ctx=ctx)b2 = nd.zeros(W2.shape[0], ctx=ctx)# 第一个全链接层W3 = nd.random_normal(shape=(400, 120), scale=.1, ctx=ctx)b3 = nd.zeros(W3.shape[1], ctx=ctx)# 第二个全链接层W4 = nd.random_normal(shape=(W3.shape[1], 84), scale=.1, ctx=ctx)b4 = nd.zeros(W4.shape[1], ctx=ctx)# 第三个全链接层W5 = nd.random_normal(shape=(W4.shape[1], 10), scale=.1, ctx=ctx)b5 = nd.zeros(W5.shape[1], ctx=ctx)params = [W1, b1, W2, b2, W3, b3, W4, b4, W5, b5]for param in params:    param.attach_grad()def net(X):    X = X.as_in_context(W1.context)    # 批量归一化    bn_X = nd.BatchNorm_v1(data=X, fix_gamma=True, eps=1e-5, output_mean_var=0.99, name='bn_X')    # 第一层卷积    h1_conv = nd.Convolution(data=bn_X, weight=W1, bias=b1, kernel=W1.shape[2:], num_filter=W1.shape[0], name='h1_conv')    # 批量归一化    bn_h1_conv = mx.sym.BatchNorm(data=h1_conv, fix_gamma=False, eps=1e-5, momentum=0.99, name='bn_h1_conv')    h1_activation = nd.relu(bn_h1_conv)    # 第二层卷集    # 批量归一化    bn_h1_conv2 = nd.BatchNorm_v1(data=h1_activation, fix_gamma=False, eps=1e-5, momentum=0.99, name='bn_h1_conv2')    h1_conv2 = nd.Convolution(data=bn_h1_conv2, weight=W2, bias=b2, kernel=W1.shape[2:], num_filter=W1.shape[0],                              name="h1_conv2")    bn_h1_conv2 = nd.BatchNorm_v1(data=h1_conv2, fix_gamma=False, eps=1e-5, momentum=0.99, name='bn_h1_conv2')    h2_activation = nd.relu(bn_h1_conv2)    # 下采样层    # 下采样层    pooling_layer_2 = mx.symbol.Pooling(data=h2_activation, kernel=(5, 5), stride=(2, 2), pad=(2, 2), pool_type='max',                                        name='pooling_layer_2')  # 16 *5 *5 flatten =    # flatten    fla = nd.flatten(data=pooling_layer_2, name='fla')    # 全链接层---1    fullcollect_layer = nd.dot(fla, W3) + b3    bn_fullcollect_layer = mx.sym.BatchNorm(data=fullcollect_layer, fix_gamma=False, eps=1e-5, momentum=0.99,                                            name='bn_fullcollect_layer')    relu_bn_fullcollect_layer = nd.relu(data=bn_fullcollect_layer)    # 全链接层-2    fullcollect_layer_2 = nd.dot(relu_bn_fullcollect_layer, W4) + b4    bn_fullcollect_layer_2 = mx.sym.BatchNorm(data=fullcollect_layer_2, fix_gamma=False, eps=1e-5, momentum=0.99,                                            name='bn_fullcollect_layer_2')    relu_bn_fullcollect_layer_2 = nd.relu(data=bn_fullcollect_layer_2)    # 全链接层3    fullcollect_layer_3 = nd.dot(relu_bn_fullcollect_layer_2, W5) + b5    bn_fullcollect_layer_3 = mx.sym.BatchNorm(data=fullcollect_layer_3, fix_gamma=False, eps=1e-5, momentum=0.99,                                              name='bn_fullcollect_layer_3')    relu_bn_fullcollect_layer_3 = nd.relu(data=bn_fullcollect_layer_3)    print('网络结构：')    print('第一个卷积层:', h1_activation.shape)    print('第二个卷积层:', h2_activation.shape)    print('下采样层:', pooling_layer_2.shape)    print('第一个全链接层:', relu_bn_fullcollect_layer.shape)    print('第二个全链接层:', relu_bn_fullcollect_layer_2.shape)    print('输出层:', relu_bn_fullcollect_layer_3.shape)    return relu_bn_fullcollect_layer_3

五、训练网络模型

数据处理了，网络模型构建好了，就可以将数据喂到网络里面去，训练网络模型了。

trick：这里需要说明一下，使用不同的组件构建的网络模型，训练的时候代码可能有点差异。这里分别针对不同组件构建的网络该如何编制训练程序进行说明。

1、如果使用上面提到的symbol组件构建的网络，那么我们就可以编制下面的程序，训练网络。

1）设置训练日志输出格式：

# 检查路径Util.check_all_path([config.saved_model_path, config.train_test_log_save_path.replace('/resnet_log.log', '')])logger = logging.getLogger()logging.basicConfig(level=logging.INFO,                    format='%(message)s',                    datefmt='%a, %d %b %Y %H:%M:%S',                    filename=config.train_test_log_save_path,                    filemode='w')

2）获取数据迭代器对象，代码：

train_data, train_label, test_data, test_label = get_all_avaliable_data(config.train_data_path,                                                                        config.train_label_path,                                                                        config.test_data_path,                                                                        config.test_label_path)data_train = Inter(config.batch_size, train_data, train_label)  # 获取训练集的迭代器对象_eval_data = Inter(config.batch_size*2, test_data, test_label)  # 获取测试集的迭代器对象

3）训练：

_eval_data = mx.sym.Variable('eval_data:')softmax_out = get_net(class_num=10, bn_mom=0.99, filter_list=[6, 16])model = mx.mod.Module(symbol=softmax_out,                      context=mx.cpu(),                      data_names=['data'],                      label_names=['softmax_label'])

model.fit(data_train,          eval_data=_eval_data,          optimizer='sgd',          initializer=mx.init.Xavier(rnd_type='gaussian', factor_type='in', magnitude=2),          eval_metric=['acc', 'ce'],          optimizer_params={'learning_rate': config.learning_rate, 'momentum': config.momentum},          batch_end_callback=mx.callback.Speedometer(config.batch_size, 1),          epoch_end_callback=mx.callback.do_checkpoint(config.saved_model_path),          num_epoch=config.num_epoch)

4) 这部分的完整代码：

import loggingimport mxnet as mxfrom net import get_netfrom tool import Inter, Testfrom util import Utilimport configfrom lodad_data import get_all_avaliable_data# 检查路径Util.check_all_path([config.saved_model_path, config.train_test_log_save_path.replace('/resnet_log.log', '')])logger = logging.getLogger()logging.basicConfig(level=logging.INFO,                    format='%(message)s',                    datefmt='%a, %d %b %Y %H:%M:%S',                    filename=config.train_test_log_save_path,                    filemode='w')if __name__ == '__main__':    """      By nxg  read only  no copy and no broadcast......    """    _eval_data = mx.sym.Variable('eval_data:')    softmax_out = get_net(class_num=10, bn_mom=0.99, filter_list=[6, 16])    model = mx.mod.Module(symbol=softmax_out,                          context=mx.cpu(),                          data_names=['data'],                          label_names=['softmax_label'])    train_data, train_label, test_data, test_label = get_all_avaliable_data(config.train_data_path,                                                                            config.train_label_path,                                                                            config.test_data_path,                                                                            config.test_label_path)    data_train = Inter(config.batch_size, train_data, train_label)  # 获取训练集的迭代器对象    _eval_data = Inter(config.batch_size*2, test_data, test_label)  # 获取测试集的迭代器对象    model.fit(data_train,              eval_data=_eval_data,              optimizer='sgd',              initializer=mx.init.Xavier(rnd_type='gaussian', factor_type='in', magnitude=2),              eval_metric=['acc', 'ce'],              optimizer_params={'learning_rate': config.learning_rate, 'momentum': config.momentum},              batch_end_callback=mx.callback.Speedometer(config.batch_size, 1),              epoch_end_callback=mx.callback.do_checkpoint(config.saved_model_path),              num_epoch=config.num_epoch)

2、如果式样上面提到的使用gluon组件构建的神经网络，那么训练网络时候的完整代码如下：

def accuracy(output, label):    return nd.mean(output.argmax(axis=1) == label).asscalar()def evaluate_accuracy(_test_data, net):    acc = 0.    for test_data_label_data_names_label_names in _test_data:        test_data = test_data_label_data_names_label_names.data        test_label = test_data_label_data_names_label_names.label        data = test_data[0].as_in_context(ctx)        label = test_label[0].as_in_context(ctx)        output = net(data)        label = label.as_in_context(ctx)        acc += accuracy(output, label)    return acc / eval_data_batch_countdef main():    train_data, train_label, test_data, test_label = get_all_avaliable_data(config.train_data_path,                                                                            config.train_label_path,                                                                            config.test_data_path,                                                                            config.test_label_path)    data_train = Inter(config.batch_size, train_data, train_label)    _eval_data = Inter(config.batch_size, test_data, test_label)    global train_data_batch_count    global eval_data_batch_count    global train_step    train_step = 0    train_data_batch_count = len(train_data) // config.batch_size  # 937    eval_data_batch_count = len(test_data) // config.batch_size  # 156    # 保存日志    log = open(file='train_test_log/resnet_log.log', mode='w')    softmax_cross_entropy_loss = gluon.loss.SoftmaxCrossEntropyLoss()    net = create_net()    net.initialize(ctx=ctx)  # 初始化网络参数    trainer = gluon.Trainer(net.collect_params(), 'sgd', {"learning_rate": 0.5})    for epoch in range(5):        all_train_loss = 0.        all_train_acc = 0.        data_train.reset()  # 这句话如果不要，那么整个数据集只会迭代一次        _eval_data.reset()  # 这句话如果不要，那么整个数据集只会迭代一次        for data_label_data_names_label_names in data_train:            train_step += 1            data = data_label_data_names_label_names.data            label = data_label_data_names_label_names.label            data = data[0].as_in_context(ctx)  # 在何种计算设备上实施计算            label = label[0].as_in_context(ctx)            with autograd.record():                output = net(data)                loss = softmax_cross_entropy_loss(output, label)            loss.backward()            trainer.step(config.batch_size)            train_loss = nd.mean(loss).asscalar()            train_acc  = accuracy(output, label)            all_train_loss += train_loss            all_train_acc += train_acc            log.writelines("Epoch:%d, train_step: %d, loss: %f, Train_acc: %f \n" %                           (epoch, train_step, train_loss, train_acc))        test_acc = evaluate_accuracy(_eval_data, net)        log.writelines("\n\nEpoch:%d, avg_train_loss: %f, avg_train_acc: %f, Test_acc: %f \n" %              (epoch, all_train_loss / train_data_batch_count, all_train_acc / train_data_batch_count, test_acc))if __name__ == '__main__':    main()

可能上面贴出的代码中的某些工具函数我并没有给全，大家可以到我的github上去下载，也可以留言，我会把完整的代码分享给大家。

6、本地保存的训练日志：

Epoch:0, train_step: 1, loss: 2.417782, Train_acc: 0.093750 Epoch:0, train_step: 2, loss: 2.147448, Train_acc: 0.218750 Epoch:0, train_step: 3, loss: 2.077140, Train_acc: 0.406250 Epoch:0, train_step: 4, loss: 1.847961, Train_acc: 0.437500 Epoch:0, train_step: 5, loss: 1.075216, Train_acc: 0.671875 Epoch:0, train_step: 6, loss: 0.592741, Train_acc: 0.859375 Epoch:0, train_step: 7, loss: 0.643913, Train_acc: 0.828125 Epoch:0, train_step: 8, loss: 0.837896, Train_acc: 0.796875 Epoch:0, train_step: 9, loss: 0.582398, Train_acc: 0.859375 Epoch:0, train_step: 10, loss: 0.750824, Train_acc: 0.765625 Epoch:0, train_step: 11, loss: 0.532329, Train_acc: 0.781250 Epoch:0, train_step: 12, loss: 0.583528, Train_acc: 0.796875 Epoch:0, train_step: 13, loss: 0.422033, Train_acc: 0.921875 Epoch:0, train_step: 14, loss: 0.829014, Train_acc: 0.718750 Epoch:0, train_step: 15, loss: 0.643326, Train_acc: 0.812500 Epoch:0, train_step: 16, loss: 0.667152, Train_acc: 0.828125 Epoch:0, train_step: 17, loss: 0.743936, Train_acc: 0.796875 Epoch:0, train_step: 18, loss: 0.640609, Train_acc: 0.718750 Epoch:0, train_step: 19, loss: 0.578947, Train_acc: 0.843750 Epoch:0, train_step: 20, loss: 0.678622, Train_acc: 0.796875 Epoch:0, train_step: 21, loss: 0.659916, Train_acc: 0.781250 Epoch:0, train_step: 22, loss: 0.886372, Train_acc: 0.703125 Epoch:0, train_step: 23, loss: 0.498017, Train_acc: 0.812500 Epoch:0, train_step: 24, loss: 0.339886, Train_acc: 0.890625 Epoch:0, train_step: 25, loss: 0.383869, Train_acc: 0.890625 Epoch:0, train_step: 26, loss: 0.352800, Train_acc: 0.890625 Epoch:0, train_step: 27, loss: 0.235351, Train_acc: 0.921875 Epoch:0, train_step: 28, loss: 0.335911, Train_acc: 0.906250 Epoch:0, train_step: 29, loss: 0.321678, Train_acc: 0.906250 Epoch:0, train_step: 30, loss: 0.214269, Train_acc: 0.937500 Epoch:0, train_step: 31, loss: 0.194405, Train_acc: 0.937500 Epoch:0, train_step: 32, loss: 0.229423, Train_acc: 0.937500 Epoch:0, train_step: 33, loss: 0.357825, Train_acc: 0.921875 Epoch:0, train_step: 34, loss: 0.093697, Train_acc: 0.984375 Epoch:0, train_step: 35, loss: 0.236372, Train_acc: 0.906250 Epoch:0, train_step: 36, loss: 0.171640, Train_acc: 0.921875 Epoch:0, train_step: 37, loss: 0.760929, Train_acc: 0.828125 Epoch:0, train_step: 38, loss: 0.425227, Train_acc: 0.890625 Epoch:0, train_step: 39, loss: 0.419191, Train_acc: 0.875000 Epoch:0, train_step: 40, loss: 0.206767, Train_acc: 0.906250 Epoch:0, train_step: 41, loss: 0.135619, Train_acc: 0.953125 Epoch:0, train_step: 42, loss: 0.359003, Train_acc: 0.875000 Epoch:0, train_step: 43, loss: 0.241495, Train_acc: 0.937500 Epoch:0, train_step: 44, loss: 0.270616, Train_acc: 0.921875 Epoch:0, train_step: 45, loss: 0.281466, Train_acc: 0.890625 Epoch:0, train_step: 46, loss: 0.263769, Train_acc: 0.921875 Epoch:0, train_step: 47, loss: 0.239509, Train_acc: 0.921875 Epoch:0, train_step: 48, loss: 0.335962, Train_acc: 0.843750 Epoch:0, train_step: 49, loss: 0.144546, Train_acc: 0.953125 Epoch:0, train_step: 50, loss: 0.116990, Train_acc: 0.953125 Epoch:0, train_step: 51, loss: 0.249545, Train_acc: 0.937500 Epoch:0, train_step: 52, loss: 0.169997, Train_acc: 0.953125 Epoch:0, train_step: 53, loss: 0.205849, Train_acc: 0.906250 Epoch:0, train_step: 54, loss: 0.181003, Train_acc: 0.937500 Epoch:0, train_step: 55, loss: 0.217988, Train_acc: 0.937500 Epoch:0, train_step: 56, loss: 0.166839, Train_acc: 0.921875 Epoch:0, train_step: 57, loss: 0.112745, Train_acc: 0.968750 Epoch:0, train_step: 58, loss: 0.518607, Train_acc: 0.890625 Epoch:0, train_step: 59, loss: 0.486200, Train_acc: 0.828125 Epoch:0, train_step: 60, loss: 0.244532, Train_acc: 0.937500 Epoch:0, train_step: 61, loss: 0.093446, Train_acc: 0.968750 Epoch:0, train_step: 62, loss: 0.193257, Train_acc: 0.953125 Epoch:0, train_step: 63, loss: 0.095059, Train_acc: 0.968750 Epoch:0, train_step: 64, loss: 0.145965, Train_acc: 0.953125 Epoch:0, train_step: 65, loss: 0.349815, Train_acc: 0.859375 Epoch:0, train_step: 66, loss: 0.148771, Train_acc: 0.953125 Epoch:0, train_step: 67, loss: 0.280851, Train_acc: 0.906250 Epoch:0, train_step: 68, loss: 0.211508, Train_acc: 0.890625 Epoch:0, train_step: 69, loss: 0.209474, Train_acc: 0.984375 Epoch:0, train_step: 70, loss: 0.249752, Train_acc: 0.953125 Epoch:0, train_step: 71, loss: 0.232584, Train_acc: 0.921875 Epoch:0, train_step: 72, loss: 0.070046, Train_acc: 0.984375 Epoch:0, train_step: 73, loss: 0.279436, Train_acc: 0.921875 Epoch:0, train_step: 74, loss: 0.147189, Train_acc: 0.953125 Epoch:0, train_step: 75, loss: 0.195968, Train_acc: 0.968750 Epoch:0, train_step: 76, loss: 0.175260, Train_acc: 0.953125 Epoch:0, train_step: 77, loss: 0.129287, Train_acc: 0.953125 Epoch:0, train_step: 78, loss: 0.249973, Train_acc: 0.921875 Epoch:0, train_step: 79, loss: 0.052008, Train_acc: 1.000000 Epoch:0, train_step: 80, loss: 0.078089, Train_acc: 0.984375 Epoch:0, train_step: 81, loss: 0.234961, Train_acc: 0.906250 Epoch:0, train_step: 82, loss: 0.114855, Train_acc: 0.953125 Epoch:0, train_step: 83, loss: 0.263273, Train_acc: 0.937500 Epoch:0, train_step: 84, loss: 0.268444, Train_acc: 0.921875 Epoch:0, train_step: 85, loss: 0.375152, Train_acc: 0.906250 Epoch:0, train_step: 86, loss: 0.190591, Train_acc: 0.921875 Epoch:0, train_step: 87, loss: 0.255328, Train_acc: 0.921875 Epoch:0, train_step: 88, loss: 0.191680, Train_acc: 0.937500 Epoch:0, train_step: 89, loss: 0.158745, Train_acc: 0.953125 Epoch:0, train_step: 90, loss: 0.178674, Train_acc: 0.921875 Epoch:0, train_step: 91, loss: 0.197587, Train_acc: 0.921875 Epoch:0, train_step: 92, loss: 0.307597, Train_acc: 0.906250 Epoch:0, train_step: 93, loss: 0.257246, Train_acc: 0.921875 Epoch:0, train_step: 94, loss: 0.151752, Train_acc: 0.937500 Epoch:0, train_step: 95, loss: 0.050518, Train_acc: 1.000000 Epoch:0, train_step: 96, loss: 0.133955, Train_acc: 0.968750 Epoch:0, train_step: 97, loss: 0.060623, Train_acc: 0.984375 Epoch:0, train_step: 98, loss: 0.170524, Train_acc: 0.937500 Epoch:0, train_step: 99, loss: 0.135782, Train_acc: 0.968750 Epoch:0, train_step: 100, loss: 0.048621, Train_acc: 0.984375 Epoch:0, train_step: 101, loss: 0.139361, Train_acc: 0.937500 Epoch:0, train_step: 102, loss: 0.209602, Train_acc: 0.921875 Epoch:0, train_step: 103, loss: 0.108424, Train_acc: 0.953125 Epoch:0, train_step: 104, loss: 0.107708, Train_acc: 0.953125 Epoch:0, train_step: 105, loss: 0.195755, Train_acc: 0.953125 Epoch:0, train_step: 106, loss: 0.047515, Train_acc: 0.984375 Epoch:0, train_step: 107, loss: 0.276701, Train_acc: 0.937500 Epoch:0, train_step: 108, loss: 0.345514, Train_acc: 0.906250 Epoch:0, train_step: 109, loss: 0.374395, Train_acc: 0.781250 Epoch:0, train_step: 110, loss: 0.395531, Train_acc: 0.906250 Epoch:0, train_step: 111, loss: 0.182749, Train_acc: 0.968750 Epoch:0, train_step: 112, loss: 0.144250, Train_acc: 0.953125 Epoch:0, train_step: 113, loss: 0.287096, Train_acc: 0.906250 Epoch:0, train_step: 114, loss: 0.494812, Train_acc: 0.859375 Epoch:0, train_step: 115, loss: 0.302390, Train_acc: 0.906250 Epoch:0, train_step: 116, loss: 0.188245, Train_acc: 0.906250 Epoch:0, train_step: 117, loss: 0.118966, Train_acc: 0.968750 Epoch:0, train_step: 118, loss: 0.181855, Train_acc: 0.953125 Epoch:0, train_step: 119, loss: 0.235975, Train_acc: 0.921875 Epoch:0, train_step: 120, loss: 0.200544, Train_acc: 0.968750 Epoch:0, train_step: 121, loss: 0.208240, Train_acc: 0.937500 Epoch:0, train_step: 122, loss: 0.304978, Train_acc: 0.906250 Epoch:0, train_step: 123, loss: 0.249742, Train_acc: 0.906250 Epoch:0, train_step: 124, loss: 0.176322, Train_acc: 0.921875 Epoch:0, train_step: 125, loss: 0.211738, Train_acc: 0.921875 Epoch:0, train_step: 126, loss: 0.107232, Train_acc: 0.968750 Epoch:0, train_step: 127, loss: 0.222557, Train_acc: 0.937500 Epoch:0, train_step: 128, loss: 0.046454, Train_acc: 0.984375 Epoch:0, train_step: 129, loss: 0.268393, Train_acc: 0.906250 Epoch:0, train_step: 130, loss: 0.170945, Train_acc: 0.937500 Epoch:0, train_step: 131, loss: 0.105138, Train_acc: 0.968750 Epoch:0, train_step: 132, loss: 0.133199, Train_acc: 0.953125 Epoch:0, train_step: 133, loss: 0.309434, Train_acc: 0.906250 Epoch:0, train_step: 134, loss: 0.133829, Train_acc: 0.984375 Epoch:0, train_step: 135, loss: 0.207350, Train_acc: 0.906250 Epoch:0, train_step: 136, loss: 0.337783, Train_acc: 0.906250 Epoch:0, train_step: 137, loss: 0.444962, Train_acc: 0.875000 Epoch:0, train_step: 138, loss: 0.143963, Train_acc: 0.953125 Epoch:0, train_step: 139, loss: 0.376271, Train_acc: 0.859375 Epoch:0, train_step: 140, loss: 0.167714, Train_acc: 0.953125 Epoch:0, train_step: 141, loss: 0.102254, Train_acc: 0.968750 Epoch:0, train_step: 142, loss: 0.042115, Train_acc: 1.000000 Epoch:0, train_step: 143, loss: 0.326979, Train_acc: 0.937500 Epoch:0, train_step: 144, loss: 0.095411, Train_acc: 0.968750 Epoch:0, train_step: 145, loss: 0.201675, Train_acc: 0.953125 Epoch:0, train_step: 146, loss: 0.159263, Train_acc: 0.953125 Epoch:0, train_step: 147, loss: 0.239955, Train_acc: 0.937500 Epoch:0, train_step: 148, loss: 0.260774, Train_acc: 0.890625 Epoch:0, train_step: 149, loss: 0.192994, Train_acc: 0.937500 Epoch:0, train_step: 150, loss: 0.218349, Train_acc: 0.921875 Epoch:0, train_step: 151, loss: 0.130956, Train_acc: 0.953125 Epoch:0, train_step: 152, loss: 0.099249, Train_acc: 0.968750 Epoch:0, train_step: 153, loss: 0.222351, Train_acc: 0.937500 Epoch:0, train_step: 154, loss: 0.048579, Train_acc: 1.000000 Epoch:0, train_step: 155, loss: 0.063588, Train_acc: 0.984375 Epoch:0, train_step: 156, loss: 0.071235, Train_acc: 0.984375 Epoch:0, train_step: 157, loss: 0.178361, Train_acc: 0.937500 Epoch:0, train_step: 158, loss: 0.200687, Train_acc: 0.953125 Epoch:0, train_step: 159, loss: 0.192534, Train_acc: 0.953125 Epoch:0, train_step: 160, loss: 0.394295, Train_acc: 0.906250 Epoch:0, train_step: 161, loss: 0.317833, Train_acc: 0.875000 Epoch:0, train_step: 162, loss: 0.064191, Train_acc: 0.968750 Epoch:0, train_step: 163, loss: 0.063043, Train_acc: 0.968750 Epoch:0, train_step: 164, loss: 0.051433, Train_acc: 0.984375 Epoch:0, train_step: 165, loss: 0.048169, Train_acc: 0.984375 Epoch:0, train_step: 166, loss: 0.023904, Train_acc: 1.000000 Epoch:0, train_step: 167, loss: 0.111142, Train_acc: 0.968750 Epoch:0, train_step: 168, loss: 0.156100, Train_acc: 0.937500 Epoch:0, train_step: 169, loss: 0.244502, Train_acc: 0.921875 Epoch:0, train_step: 170, loss: 0.129055, Train_acc: 0.984375 Epoch:0, train_step: 171, loss: 0.046237, Train_acc: 1.000000 Epoch:0, train_step: 172, loss: 0.183251, Train_acc: 0.968750 Epoch:0, train_step: 173, loss: 0.117667, Train_acc: 0.937500 Epoch:0, train_step: 174, loss: 0.093352, Train_acc: 0.984375 Epoch:0, train_step: 175, loss: 0.072180, Train_acc: 0.968750 Epoch:0, train_step: 176, loss: 0.241708, Train_acc: 0.937500 Epoch:0, train_step: 177, loss: 0.061940, Train_acc: 0.984375 Epoch:0, train_step: 178, loss: 0.099466, Train_acc: 0.968750 Epoch:0, train_step: 179, loss: 0.055113, Train_acc: 0.968750 Epoch:0, train_step: 180, loss: 0.076228, Train_acc: 0.968750 Epoch:0, train_step: 181, loss: 0.268029, Train_acc: 0.906250 Epoch:0, train_step: 182, loss: 0.107267, Train_acc: 0.984375 Epoch:0, train_step: 183, loss: 0.137517, Train_acc: 0.968750 Epoch:0, train_step: 184, loss: 0.081613, Train_acc: 0.953125 Epoch:0, train_step: 185, loss: 0.097723, Train_acc: 0.984375 Epoch:0, train_step: 186, loss: 0.173998, Train_acc: 0.937500 Epoch:0, train_step: 187, loss: 0.111674, Train_acc: 0.937500 Epoch:0, train_step: 188, loss: 0.133634, Train_acc: 0.953125 Epoch:0, train_step: 189, loss: 0.240766, Train_acc: 0.921875 Epoch:0, train_step: 190, loss: 0.071469, Train_acc: 0.968750 Epoch:0, train_step: 191, loss: 0.085162, Train_acc: 0.953125 Epoch:0, train_step: 192, loss: 0.201763, Train_acc: 0.937500 Epoch:0, train_step: 193, loss: 0.087841, Train_acc: 0.968750 Epoch:0, train_step: 194, loss: 0.186591, Train_acc: 0.937500 Epoch:0, train_step: 195, loss: 0.056906, Train_acc: 0.984375 Epoch:0, train_step: 196, loss: 0.078472, Train_acc: 0.984375 Epoch:0, train_step: 197, loss: 0.285432, Train_acc: 0.953125 Epoch:0, train_step: 198, loss: 0.299019, Train_acc: 0.890625 Epoch:0, train_step: 199, loss: 0.099036, Train_acc: 0.984375 Epoch:0, train_step: 200, loss: 0.212280, Train_acc: 0.937500 Epoch:0, train_step: 201, loss: 0.111627, Train_acc: 0.953125 Epoch:0, train_step: 202, loss: 0.195275, Train_acc: 0.953125 Epoch:0, train_step: 203, loss: 0.268554, Train_acc: 0.937500 Epoch:0, train_step: 204, loss: 0.202567, Train_acc: 0.937500 Epoch:0, train_step: 205, loss: 0.269112, Train_acc: 0.921875 Epoch:0, train_step: 206, loss: 0.245677, Train_acc: 0.906250 Epoch:0, train_step: 207, loss: 0.137429, Train_acc: 0.921875 Epoch:0, train_step: 208, loss: 0.137760, Train_acc: 0.968750 Epoch:0, train_step: 209, loss: 0.043124, Train_acc: 1.000000 Epoch:0, train_step: 210, loss: 0.206140, Train_acc: 0.937500 Epoch:0, train_step: 211, loss: 0.089152, Train_acc: 0.984375 Epoch:0, train_step: 212, loss: 0.152733, Train_acc: 0.953125 Epoch:0, train_step: 213, loss: 0.110357, Train_acc: 0.953125 Epoch:0, train_step: 214, loss: 0.096450, Train_acc: 0.984375 Epoch:0, train_step: 215, loss: 0.254843, Train_acc: 0.921875 Epoch:0, train_step: 216, loss: 0.053830, Train_acc: 1.000000 Epoch:0, train_step: 217, loss: 0.171203, Train_acc: 0.953125 Epoch:0, train_step: 218, loss: 0.254211, Train_acc: 0.937500 Epoch:0, train_step: 219, loss: 0.187960, Train_acc: 0.953125 Epoch:0, train_step: 220, loss: 0.135573, Train_acc: 0.953125 Epoch:0, train_step: 221, loss: 0.152126, Train_acc: 0.921875 Epoch:0, train_step: 222, loss: 0.167882, Train_acc: 0.937500 Epoch:0, train_step: 223, loss: 0.252212, Train_acc: 0.937500 Epoch:0, train_step: 224, loss: 0.200252, Train_acc: 0.921875 Epoch:0, train_step: 225, loss: 0.325268, Train_acc: 0.890625 Epoch:0, train_step: 226, loss: 0.055470, Train_acc: 0.984375 Epoch:0, train_step: 227, loss: 0.035767, Train_acc: 1.000000 Epoch:0, train_step: 228, loss: 0.238885, Train_acc: 0.937500 Epoch:0, train_step: 229, loss: 0.068784, Train_acc: 0.968750 Epoch:0, train_step: 230, loss: 0.166429, Train_acc: 0.953125 Epoch:0, train_step: 231, loss: 0.160921, Train_acc: 0.953125 Epoch:0, train_step: 232, loss: 0.242600, Train_acc: 0.921875 Epoch:0, train_step: 233, loss: 0.029633, Train_acc: 1.000000 Epoch:0, train_step: 234, loss: 0.056294, Train_acc: 0.984375 Epoch:0, train_step: 235, loss: 0.023245, Train_acc: 0.984375 Epoch:0, train_step: 236, loss: 0.048721, Train_acc: 0.984375 Epoch:0, train_step: 237, loss: 0.072512, Train_acc: 0.968750 Epoch:0, train_step: 238, loss: 0.056075, Train_acc: 0.968750 Epoch:0, train_step: 239, loss: 0.114910, Train_acc: 0.953125 Epoch:0, train_step: 240, loss: 0.076293, Train_acc: 0.984375 Epoch:0, train_step: 241, loss: 0.092031, Train_acc: 0.953125 Epoch:0, train_step: 242, loss: 0.095848, Train_acc: 0.953125 Epoch:0, train_step: 243, loss: 0.104798, Train_acc: 0.968750 Epoch:0, train_step: 244, loss: 0.108040, Train_acc: 0.968750 Epoch:0, train_step: 245, loss: 0.071164, Train_acc: 0.984375 Epoch:0, train_step: 246, loss: 0.031898, Train_acc: 1.000000 Epoch:0, train_step: 247, loss: 0.176472, Train_acc: 0.937500 Epoch:0, train_step: 248, loss: 0.125027, Train_acc: 0.968750 Epoch:0, train_step: 249, loss: 0.144656, Train_acc: 0.968750 Epoch:0, train_step: 250, loss: 0.164103, Train_acc: 0.937500 Epoch:0, train_step: 251, loss: 0.097101, Train_acc: 0.984375 Epoch:0, train_step: 252, loss: 0.064158, Train_acc: 0.984375 Epoch:0, train_step: 253, loss: 0.042128, Train_acc: 0.984375 Epoch:0, train_step: 254, loss: 0.094065, Train_acc: 0.953125 Epoch:0, train_step: 255, loss: 0.053626, Train_acc: 0.984375 Epoch:0, train_step: 256, loss: 0.042115, Train_acc: 0.984375 Epoch:0, train_step: 257, loss: 0.044252, Train_acc: 1.000000 Epoch:0, train_step: 258, loss: 0.129825, Train_acc: 0.984375 Epoch:0, train_step: 259, loss: 0.128804, Train_acc: 0.984375 Epoch:0, train_step: 260, loss: 0.015984, Train_acc: 1.000000 Epoch:0, train_step: 261, loss: 0.138158, Train_acc: 0.937500 Epoch:0, train_step: 262, loss: 0.268613, Train_acc: 0.953125 Epoch:0, train_step: 263, loss: 0.181672, Train_acc: 0.921875 Epoch:0, train_step: 264, loss: 0.127224, Train_acc: 0.968750 Epoch:0, train_step: 265, loss: 0.159336, Train_acc: 0.953125 Epoch:0, train_step: 266, loss: 0.251801, Train_acc: 0.890625 Epoch:0, train_step: 267, loss: 0.094569, Train_acc: 0.968750 Epoch:0, train_step: 268, loss: 0.160217, Train_acc: 0.984375 Epoch:0, train_step: 269, loss: 0.076990, Train_acc: 0.968750 Epoch:0, train_step: 270, loss: 0.243788, Train_acc: 0.937500 Epoch:0, train_step: 271, loss: 0.115324, Train_acc: 0.968750 Epoch:0, train_step: 272, loss: 0.035700, Train_acc: 1.000000 Epoch:0, train_step: 273, loss: 0.149722, Train_acc: 0.953125 Epoch:0, train_step: 274, loss: 0.154545, Train_acc: 0.953125 Epoch:0, train_step: 275, loss: 0.433616, Train_acc: 0.937500 Epoch:0, train_step: 276, loss: 0.087909, Train_acc: 0.984375 Epoch:0, train_step: 277, loss: 0.228504, Train_acc: 0.921875 Epoch:0, train_step: 278, loss: 0.125605, Train_acc: 0.953125 Epoch:0, train_step: 279, loss: 0.152510, Train_acc: 0.937500 Epoch:0, train_step: 280, loss: 0.129510, Train_acc: 0.968750 Epoch:0, train_step: 281, loss: 0.213520, Train_acc: 0.953125 Epoch:0, train_step: 282, loss: 0.117308, Train_acc: 0.984375 Epoch:0, train_step: 283, loss: 0.102311, Train_acc: 0.968750 Epoch:0, train_step: 284, loss: 0.127585, Train_acc: 0.953125 Epoch:0, train_step: 285, loss: 0.052507, Train_acc: 0.984375 Epoch:0, train_step: 286, loss: 0.139868, Train_acc: 0.968750 Epoch:0, train_step: 287, loss: 0.088044, Train_acc: 0.968750 Epoch:0, train_step: 288, loss: 0.138713, Train_acc: 0.953125 Epoch:0, train_step: 289, loss: 0.077087, Train_acc: 0.953125 Epoch:0, train_step: 290, loss: 0.019821, Train_acc: 1.000000 Epoch:0, train_step: 291, loss: 0.073906, Train_acc: 0.968750 Epoch:0, train_step: 292, loss: 0.074876, Train_acc: 0.968750 Epoch:0, train_step: 293, loss: 0.092380, Train_acc: 0.953125 Epoch:0, train_step: 294, loss: 0.075615, Train_acc: 0.968750 Epoch:0, train_step: 295, loss: 0.148927, Train_acc: 0.968750 Epoch:0, train_step: 296, loss: 0.029515, Train_acc: 0.984375 Epoch:0, train_step: 297, loss: 0.019095, Train_acc: 1.000000 Epoch:0, train_step: 298, loss: 0.065494, Train_acc: 0.968750 Epoch:0, train_step: 299, loss: 0.140963, Train_acc: 0.953125 Epoch:0, train_step: 300, loss: 0.072603, Train_acc: 0.953125 Epoch:0, train_step: 301, loss: 0.223620, Train_acc: 0.953125 Epoch:0, train_step: 302, loss: 0.077674, Train_acc: 0.984375 Epoch:0, train_step: 303, loss: 0.220717, Train_acc: 0.937500 Epoch:0, train_step: 304, loss: 0.191390, Train_acc: 0.921875 Epoch:0, train_step: 305, loss: 0.050194, Train_acc: 0.984375 Epoch:0, train_step: 306, loss: 0.062399, Train_acc: 0.984375 Epoch:0, train_step: 307, loss: 0.084981, Train_acc: 0.968750 Epoch:0, train_step: 308, loss: 0.024511, Train_acc: 1.000000 Epoch:0, train_step: 309, loss: 0.041777, Train_acc: 0.984375 Epoch:0, train_step: 310, loss: 0.064886, Train_acc: 0.968750 Epoch:0, train_step: 311, loss: 0.082824, Train_acc: 1.000000 Epoch:0, train_step: 312, loss: 0.069902, Train_acc: 0.984375 Epoch:0, train_step: 313, loss: 0.054433, Train_acc: 0.968750 Epoch:0, train_step: 314, loss: 0.155064, Train_acc: 0.968750 Epoch:0, train_step: 315, loss: 0.101214, Train_acc: 0.968750 Epoch:0, train_step: 316, loss: 0.286334, Train_acc: 0.921875 Epoch:0, train_step: 317, loss: 0.156658, Train_acc: 0.953125 Epoch:0, train_step: 318, loss: 0.054001, Train_acc: 0.968750 Epoch:0, train_step: 319, loss: 0.020793, Train_acc: 1.000000 Epoch:0, train_step: 320, loss: 0.071518, Train_acc: 0.968750 Epoch:0, train_step: 321, loss: 0.055152, Train_acc: 0.984375 Epoch:0, train_step: 322, loss: 0.189750, Train_acc: 0.968750 Epoch:0, train_step: 323, loss: 0.095044, Train_acc: 0.968750 Epoch:0, train_step: 324, loss: 0.158666, Train_acc: 0.953125 Epoch:0, train_step: 325, loss: 0.368647, Train_acc: 0.937500 Epoch:0, train_step: 326, loss: 0.095455, Train_acc: 0.968750 Epoch:0, train_step: 327, loss: 0.064338, Train_acc: 0.968750 Epoch:0, train_step: 328, loss: 0.052826, Train_acc: 0.984375 Epoch:0, train_step: 329, loss: 0.066039, Train_acc: 0.953125 Epoch:0, train_step: 330, loss: 0.023802, Train_acc: 1.000000 Epoch:0, train_step: 331, loss: 0.114402, Train_acc: 0.968750 Epoch:0, train_step: 332, loss: 0.094503, Train_acc: 0.937500 Epoch:0, train_step: 333, loss: 0.028623, Train_acc: 0.984375 Epoch:0, train_step: 334, loss: 0.081858, Train_acc: 0.984375 Epoch:0, train_step: 335, loss: 0.116041, Train_acc: 0.968750 Epoch:0, train_step: 336, loss: 0.078752, Train_acc: 0.984375 Epoch:0, train_step: 337, loss: 0.038451, Train_acc: 0.984375 Epoch:0, train_step: 338, loss: 0.160037, Train_acc: 0.953125 Epoch:0, train_step: 339, loss: 0.072961, Train_acc: 0.984375 Epoch:0, train_step: 340, loss: 0.058824, Train_acc: 0.984375 Epoch:0, train_step: 341, loss: 0.060204, Train_acc: 0.968750 Epoch:0, train_step: 342, loss: 0.052586, Train_acc: 0.984375 Epoch:0, train_step: 343, loss: 0.100275, Train_acc: 0.953125 Epoch:0, train_step: 344, loss: 0.069342, Train_acc: 0.968750 Epoch:0, train_step: 345, loss: 0.041397, Train_acc: 0.984375 Epoch:0, train_step: 346, loss: 0.114980, Train_acc: 0.953125 Epoch:0, train_step: 347, loss: 0.080326, Train_acc: 0.968750 Epoch:0, train_step: 348, loss: 0.111050, Train_acc: 0.953125 Epoch:0, train_step: 349, loss: 0.192234, Train_acc: 0.968750 Epoch:0, train_step: 350, loss: 0.032916, Train_acc: 1.000000 Epoch:0, train_step: 351, loss: 0.112401, Train_acc: 0.953125 Epoch:0, train_step: 352, loss: 0.195880, Train_acc: 0.921875 Epoch:0, train_step: 353, loss: 0.172978, Train_acc: 0.921875 Epoch:0, train_step: 354, loss: 0.065239, Train_acc: 0.984375 Epoch:0, train_step: 355, loss: 0.095926, Train_acc: 0.968750 Epoch:0, train_step: 356, loss: 0.128848, Train_acc: 0.968750 Epoch:0, train_step: 357, loss: 0.034309, Train_acc: 1.000000 Epoch:0, train_step: 358, loss: 0.150101, Train_acc: 0.968750 Epoch:0, train_step: 359, loss: 0.009141, Train_acc: 1.000000 Epoch:0, train_step: 360, loss: 0.019325, Train_acc: 1.000000 Epoch:0, train_step: 361, loss: 0.102030, Train_acc: 0.968750 Epoch:0, train_step: 362, loss: 0.038026, Train_acc: 1.000000 Epoch:0, train_step: 363, loss: 0.030194, Train_acc: 0.984375 Epoch:0, train_step: 364, loss: 0.009579, Train_acc: 1.000000 Epoch:0, train_step: 365, loss: 0.015169, Train_acc: 1.000000 Epoch:0, train_step: 366, loss: 0.076359, Train_acc: 0.968750 Epoch:0, train_step: 367, loss: 0.081349, Train_acc: 0.984375 Epoch:0, train_step: 368, loss: 0.018403, Train_acc: 1.000000 Epoch:0, train_step: 369, loss: 0.063860, Train_acc: 0.968750 Epoch:0, train_step: 370, loss: 0.068194, Train_acc: 0.984375 Epoch:0, train_step: 371, loss: 0.216741, Train_acc: 0.937500 Epoch:0, train_step: 372, loss: 0.011690, Train_acc: 1.000000 Epoch:0, train_step: 373, loss: 0.093802, Train_acc: 0.968750 Epoch:0, train_step: 374, loss: 0.125502, Train_acc: 0.984375 Epoch:0, train_step: 375, loss: 0.068067, Train_acc: 0.984375 Epoch:0, train_step: 376, loss: 0.043508, Train_acc: 1.000000 Epoch:0, train_step: 377, loss: 0.073455, Train_acc: 0.968750 Epoch:0, train_step: 378, loss: 0.031747, Train_acc: 0.984375 Epoch:0, train_step: 379, loss: 0.034784, Train_acc: 1.000000 Epoch:0, train_step: 380, loss: 0.120828, Train_acc: 0.937500 Epoch:0, train_step: 381, loss: 0.007451, Train_acc: 1.000000 Epoch:0, train_step: 382, loss: 0.035504, Train_acc: 0.984375 Epoch:0, train_step: 383, loss: 0.176988, Train_acc: 0.921875 Epoch:0, train_step: 384, loss: 0.112157, Train_acc: 0.968750 Epoch:0, train_step: 385, loss: 0.105336, Train_acc: 0.968750 Epoch:0, train_step: 386, loss: 0.159342, Train_acc: 0.953125 Epoch:0, train_step: 387, loss: 0.060455, Train_acc: 0.984375 Epoch:0, train_step: 388, loss: 0.202737, Train_acc: 0.953125 Epoch:0, train_step: 389, loss: 0.063931, Train_acc: 1.000000 Epoch:0, train_step: 390, loss: 0.112387, Train_acc: 0.937500 Epoch:0, train_step: 391, loss: 0.018849, Train_acc: 1.000000 Epoch:0, train_step: 392, loss: 0.049208, Train_acc: 0.984375 Epoch:0, train_step: 393, loss: 0.089838, Train_acc: 0.968750 Epoch:0, train_step: 394, loss: 0.073714, Train_acc: 0.984375 Epoch:0, train_step: 395, loss: 0.133020, Train_acc: 0.937500 Epoch:0, train_step: 396, loss: 0.039155, Train_acc: 1.000000 Epoch:0, train_step: 397, loss: 0.022785, Train_acc: 0.984375 Epoch:0, train_step: 398, loss: 0.007015, Train_acc: 1.000000 Epoch:0, train_step: 399, loss: 0.077164, Train_acc: 0.984375 Epoch:0, train_step: 400, loss: 0.100587, Train_acc: 0.968750 Epoch:0, train_step: 401, loss: 0.040362, Train_acc: 0.984375 Epoch:0, train_step: 402, loss: 0.129088, Train_acc: 0.984375 Epoch:0, train_step: 403, loss: 0.172486, Train_acc: 0.953125 Epoch:0, train_step: 404, loss: 0.211238, Train_acc: 0.921875 Epoch:0, train_step: 405, loss: 0.077606, Train_acc: 0.968750 Epoch:0, train_step: 406, loss: 0.091099, Train_acc: 0.968750 Epoch:0, train_step: 407, loss: 0.176847, Train_acc: 0.953125 Epoch:0, train_step: 408, loss: 0.036967, Train_acc: 0.984375 Epoch:0, train_step: 409, loss: 0.104191, Train_acc: 0.953125 Epoch:0, train_step: 410, loss: 0.092425, Train_acc: 0.953125 Epoch:0, train_step: 411, loss: 0.123813, Train_acc: 0.953125 Epoch:0, train_step: 412, loss: 0.078018, Train_acc: 0.968750 Epoch:0, train_step: 413, loss: 0.261442, Train_acc: 0.906250 Epoch:0, train_step: 414, loss: 0.092718, Train_acc: 0.953125 Epoch:0, train_step: 415, loss: 0.109427, Train_acc: 0.984375 Epoch:0, train_step: 416, loss: 0.146410, Train_acc: 0.953125 Epoch:0, train_step: 417, loss: 0.255953, Train_acc: 0.937500 Epoch:0, train_step: 418, loss: 0.304967, Train_acc: 0.890625 Epoch:0, train_step: 419, loss: 0.114228, Train_acc: 0.953125 Epoch:0, train_step: 420, loss: 0.167067, Train_acc: 0.968750 Epoch:0, train_step: 421, loss: 0.136056, Train_acc: 0.953125 Epoch:0, train_step: 422, loss: 0.012798, Train_acc: 1.000000 Epoch:0, train_step: 423, loss: 0.096626, Train_acc: 0.968750 Epoch:0, train_step: 424, loss: 0.043080, Train_acc: 0.984375 Epoch:0, train_step: 425, loss: 0.226755, Train_acc: 0.937500 Epoch:0, train_step: 426, loss: 0.160724, Train_acc: 0.968750 Epoch:0, train_step: 427, loss: 0.035260, Train_acc: 1.000000 Epoch:0, train_step: 428, loss: 0.041816, Train_acc: 0.984375 Epoch:0, train_step: 429, loss: 0.036927, Train_acc: 1.000000 Epoch:0, train_step: 430, loss: 0.220532, Train_acc: 0.921875 Epoch:0, train_step: 431, loss: 0.093938, Train_acc: 0.984375 Epoch:0, train_step: 432, loss: 0.024433, Train_acc: 1.000000 Epoch:0, train_step: 433, loss: 0.089946, Train_acc: 0.984375 Epoch:0, train_step: 434, loss: 0.033896, Train_acc: 1.000000 Epoch:0, train_step: 435, loss: 0.101276, Train_acc: 0.984375 Epoch:0, train_step: 436, loss: 0.062610, Train_acc: 0.968750 Epoch:0, train_step: 437, loss: 0.054586, Train_acc: 0.984375 Epoch:0, train_step: 438, loss: 0.128054, Train_acc: 0.984375 Epoch:0, train_step: 439, loss: 0.015394, Train_acc: 1.000000 Epoch:0, train_step: 440, loss: 0.089927, Train_acc: 0.968750 Epoch:0, train_step: 441, loss: 0.061562, Train_acc: 0.968750 Epoch:0, train_step: 442, loss: 0.070417, Train_acc: 0.984375 Epoch:0, train_step: 443, loss: 0.013599, Train_acc: 1.000000 Epoch:0, train_step: 444, loss: 0.158696, Train_acc: 0.937500 Epoch:0, train_step: 445, loss: 0.039054, Train_acc: 0.984375 Epoch:0, train_step: 446, loss: 0.158124, Train_acc: 0.937500 Epoch:0, train_step: 447, loss: 0.114853, Train_acc: 0.968750 Epoch:0, train_step: 448, loss: 0.330460, Train_acc: 0.921875 Epoch:0, train_step: 449, loss: 0.144149, Train_acc: 0.984375 Epoch:0, train_step: 450, loss: 0.077496, Train_acc: 0.968750 Epoch:0, train_step: 451, loss: 0.061755, Train_acc: 0.984375 Epoch:0, train_step: 452, loss: 0.015045, Train_acc: 1.000000 Epoch:0, train_step: 453, loss: 0.101570, Train_acc: 0.984375 Epoch:0, train_step: 454, loss: 0.132750, Train_acc: 0.968750 Epoch:0, train_step: 455, loss: 0.099636, Train_acc: 0.984375 Epoch:0, train_step: 456, loss: 0.123801, Train_acc: 0.968750 Epoch:0, train_step: 457, loss: 0.126693, Train_acc: 0.937500 Epoch:0, train_step: 458, loss: 0.056973, Train_acc: 0.984375 Epoch:0, train_step: 459, loss: 0.055550, Train_acc: 0.968750 Epoch:0, train_step: 460, loss: 0.010900, Train_acc: 1.000000 Epoch:0, train_step: 461, loss: 0.043595, Train_acc: 0.984375 Epoch:0, train_step: 462, loss: 0.006496, Train_acc: 1.000000 Epoch:0, train_step: 463, loss: 0.055602, Train_acc: 0.984375 Epoch:0, train_step: 464, loss: 0.028079, Train_acc: 1.000000 Epoch:0, train_step: 465, loss: 0.253337, Train_acc: 0.953125 Epoch:0, train_step: 466, loss: 0.079758, Train_acc: 0.968750 Epoch:0, train_step: 467, loss: 0.069280, Train_acc: 0.968750 Epoch:0, train_step: 468, loss: 0.087992, Train_acc: 0.953125 Epoch:0, train_step: 469, loss: 0.147397, Train_acc: 0.953125 Epoch:0, train_step: 470, loss: 0.153349, Train_acc: 0.937500 Epoch:0, train_step: 471, loss: 0.113429, Train_acc: 0.984375 Epoch:0, train_step: 472, loss: 0.114258, Train_acc: 0.968750 Epoch:0, train_step: 473, loss: 0.062503, Train_acc: 0.968750 Epoch:0, train_step: 474, loss: 0.046547, Train_acc: 0.968750 Epoch:0, train_step: 475, loss: 0.036787, Train_acc: 0.984375 Epoch:0, train_step: 476, loss: 0.044965, Train_acc: 0.984375 Epoch:0, train_step: 477, loss: 0.077935, Train_acc: 0.984375 Epoch:0, train_step: 478, loss: 0.061722, Train_acc: 0.968750 Epoch:0, train_step: 479, loss: 0.188490, Train_acc: 0.953125 Epoch:0, train_step: 480, loss: 0.082066, Train_acc: 0.953125 Epoch:0, train_step: 481, loss: 0.037588, Train_acc: 0.984375 Epoch:0, train_step: 482, loss: 0.127670, Train_acc: 0.968750 Epoch:0, train_step: 483, loss: 0.102800, Train_acc: 0.968750 Epoch:0, train_step: 484, loss: 0.130782, Train_acc: 0.968750 Epoch:0, train_step: 485, loss: 0.044936, Train_acc: 0.984375 Epoch:0, train_step: 486, loss: 0.062258, Train_acc: 0.968750 Epoch:0, train_step: 487, loss: 0.084022, Train_acc: 0.984375 Epoch:0, train_step: 488, loss: 0.171461, Train_acc: 0.968750 Epoch:0, train_step: 489, loss: 0.072823, Train_acc: 0.968750 Epoch:0, train_step: 490, loss: 0.104410, Train_acc: 0.968750 Epoch:0, train_step: 491, loss: 0.111852, Train_acc: 0.937500 Epoch:0, train_step: 492, loss: 0.031321, Train_acc: 0.984375 Epoch:0, train_step: 493, loss: 0.041359, Train_acc: 0.984375 Epoch:0, train_step: 494, loss: 0.122622, Train_acc: 0.984375 Epoch:0, train_step: 495, loss: 0.277428, Train_acc: 0.921875 Epoch:0, train_step: 496, loss: 0.228413, Train_acc: 0.937500 Epoch:0, train_step: 497, loss: 0.079994, Train_acc: 0.968750 Epoch:0, train_step: 498, loss: 0.111047, Train_acc: 0.937500 Epoch:0, train_step: 499, loss: 0.004568, Train_acc: 1.000000 Epoch:0, train_step: 500, loss: 0.102676, Train_acc: 0.953125 Epoch:0, train_step: 501, loss: 0.210133, Train_acc: 0.921875 Epoch:0, train_step: 502, loss: 0.127958, Train_acc: 0.968750 Epoch:0, train_step: 503, loss: 0.076221, Train_acc: 0.968750 Epoch:0, train_step: 504, loss: 0.061081, Train_acc: 0.984375 Epoch:0, train_step: 505, loss: 0.076232, Train_acc: 0.968750 Epoch:0, train_step: 506, loss: 0.320697, Train_acc: 0.937500 Epoch:0, train_step: 507, loss: 0.183642, Train_acc: 0.921875 Epoch:0, train_step: 508, loss: 0.086130, Train_acc: 0.953125 Epoch:0, train_step: 509, loss: 0.149942, Train_acc: 0.968750 Epoch:0, train_step: 510, loss: 0.045698, Train_acc: 0.984375 Epoch:0, train_step: 511, loss: 0.159423, Train_acc: 0.953125 Epoch:0, train_step: 512, loss: 0.116437, Train_acc: 0.968750 Epoch:0, train_step: 513, loss: 0.070719, Train_acc: 0.984375 Epoch:0, train_step: 514, loss: 0.072158, Train_acc: 0.984375 Epoch:0, train_step: 515, loss: 0.055333, Train_acc: 0.984375 Epoch:0, train_step: 516, loss: 0.018247, Train_acc: 1.000000 Epoch:0, train_step: 517, loss: 0.077992, Train_acc: 0.968750 Epoch:0, train_step: 518, loss: 0.030270, Train_acc: 1.000000 Epoch:0, train_step: 519, loss: 0.022985, Train_acc: 1.000000 Epoch:0, train_step: 520, loss: 0.136720, Train_acc: 0.953125 Epoch:0, train_step: 521, loss: 0.109290, Train_acc: 0.953125 Epoch:0, train_step: 522, loss: 0.151819, Train_acc: 0.968750 Epoch:0, train_step: 523, loss: 0.106009, Train_acc: 0.968750 Epoch:0, train_step: 524, loss: 0.038539, Train_acc: 0.984375 Epoch:0, train_step: 525, loss: 0.060333, Train_acc: 0.984375 Epoch:0, train_step: 526, loss: 0.032669, Train_acc: 0.984375 Epoch:0, train_step: 527, loss: 0.106597, Train_acc: 0.968750 Epoch:0, train_step: 528, loss: 0.213871, Train_acc: 0.968750 Epoch:0, train_step: 529, loss: 0.012281, Train_acc: 1.000000 Epoch:0, train_step: 530, loss: 0.013119, Train_acc: 1.000000 Epoch:0, train_step: 531, loss: 0.007509, Train_acc: 1.000000 Epoch:0, train_step: 532, loss: 0.052356, Train_acc: 0.984375 Epoch:0, train_step: 533, loss: 0.090982, Train_acc: 0.968750 Epoch:0, train_step: 534, loss: 0.049310, Train_acc: 0.984375 Epoch:0, train_step: 535, loss: 0.039202, Train_acc: 1.000000 Epoch:0, train_step: 536, loss: 0.008112, Train_acc: 1.000000 Epoch:0, train_step: 537, loss: 0.068421, Train_acc: 0.968750 Epoch:0, train_step: 538, loss: 0.237720, Train_acc: 0.953125 Epoch:0, train_step: 539, loss: 0.118948, Train_acc: 0.984375 Epoch:0, train_step: 540, loss: 0.060209, Train_acc: 0.953125 Epoch:0, train_step: 541, loss: 0.016179, Train_acc: 1.000000 Epoch:0, train_step: 542, loss: 0.290211, Train_acc: 0.906250 Epoch:0, train_step: 543, loss: 0.171227, Train_acc: 0.968750 Epoch:0, train_step: 544, loss: 0.140518, Train_acc: 0.953125 Epoch:0, train_step: 545, loss: 0.251154, Train_acc: 0.937500 Epoch:0, train_step: 546, loss: 0.183961, Train_acc: 0.953125 Epoch:0, train_step: 547, loss: 0.059304, Train_acc: 0.984375 Epoch:0, train_step: 548, loss: 0.122908, Train_acc: 0.953125 Epoch:0, train_step: 549, loss: 0.035064, Train_acc: 0.984375 Epoch:0, train_step: 550, loss: 0.172791, Train_acc: 0.953125 Epoch:0, train_step: 551, loss: 0.164842, Train_acc: 0.937500 Epoch:0, train_step: 552, loss: 0.029545, Train_acc: 1.000000 Epoch:0, train_step: 553, loss: 0.083210, Train_acc: 0.953125 Epoch:0, train_step: 554, loss: 0.111726, Train_acc: 0.937500 Epoch:0, train_step: 555, loss: 0.184524, Train_acc: 0.953125 Epoch:0, train_step: 556, loss: 0.034597, Train_acc: 0.984375 Epoch:0, train_step: 557, loss: 0.138710, Train_acc: 0.968750 Epoch:0, train_step: 558, loss: 0.064175, Train_acc: 0.968750 Epoch:0, train_step: 559, loss: 0.081560, Train_acc: 0.968750 Epoch:0, train_step: 560, loss: 0.016800, Train_acc: 1.000000 Epoch:0, train_step: 561, loss: 0.056946, Train_acc: 0.984375 Epoch:0, train_step: 562, loss: 0.045096, Train_acc: 0.984375 Epoch:0, train_step: 563, loss: 0.075772, Train_acc: 0.984375 Epoch:0, train_step: 564, loss: 0.024036, Train_acc: 0.984375 Epoch:0, train_step: 565, loss: 0.124630, Train_acc: 0.953125 Epoch:0, train_step: 566, loss: 0.153204, Train_acc: 0.953125 Epoch:0, train_step: 567, loss: 0.061613, Train_acc: 0.984375 Epoch:0, train_step: 568, loss: 0.008488, Train_acc: 1.000000 Epoch:0, train_step: 569, loss: 0.121490, Train_acc: 0.953125 Epoch:0, train_step: 570, loss: 0.143453, Train_acc: 0.937500 Epoch:0, train_step: 571, loss: 0.050782, Train_acc: 0.984375 Epoch:0, train_step: 572, loss: 0.022803, Train_acc: 1.000000 Epoch:0, train_step: 573, loss: 0.060813, Train_acc: 0.984375 Epoch:0, train_step: 574, loss: 0.104174, Train_acc: 0.968750 Epoch:0, train_step: 575, loss: 0.136626, Train_acc: 0.968750 Epoch:0, train_step: 576, loss: 0.026158, Train_acc: 1.000000 Epoch:0, train_step: 577, loss: 0.060746, Train_acc: 0.968750 Epoch:0, train_step: 578, loss: 0.100456, Train_acc: 0.968750 Epoch:0, train_step: 579, loss: 0.185428, Train_acc: 0.968750 Epoch:0, train_step: 580, loss: 0.129234, Train_acc: 0.968750 Epoch:0, train_step: 581, loss: 0.111153, Train_acc: 0.968750 Epoch:0, train_step: 582, loss: 0.031291, Train_acc: 0.984375 Epoch:0, train_step: 583, loss: 0.080749, Train_acc: 0.984375 Epoch:0, train_step: 584, loss: 0.081667, Train_acc: 0.984375 Epoch:0, train_step: 585, loss: 0.197980, Train_acc: 0.953125 Epoch:0, train_step: 586, loss: 0.113007, Train_acc: 0.968750 Epoch:0, train_step: 587, loss: 0.059985, Train_acc: 1.000000 Epoch:0, train_step: 588, loss: 0.016323, Train_acc: 1.000000 Epoch:0, train_step: 589, loss: 0.060359, Train_acc: 0.984375 Epoch:0, train_step: 590, loss: 0.135560, Train_acc: 0.953125 Epoch:0, train_step: 591, loss: 0.093629, Train_acc: 0.968750 Epoch:0, train_step: 592, loss: 0.187749, Train_acc: 0.968750 Epoch:0, train_step: 593, loss: 0.022493, Train_acc: 1.000000 Epoch:0, train_step: 594, loss: 0.043936, Train_acc: 1.000000 Epoch:0, train_step: 595, loss: 0.033467, Train_acc: 0.984375 Epoch:0, train_step: 596, loss: 0.021363, Train_acc: 1.000000 Epoch:0, train_step: 597, loss: 0.018345, Train_acc: 1.000000 Epoch:0, train_step: 598, loss: 0.018057, Train_acc: 1.000000 Epoch:0, train_step: 599, loss: 0.058234, Train_acc: 0.968750 Epoch:0, train_step: 600, loss: 0.115282, Train_acc: 0.984375 Epoch:0, train_step: 601, loss: 0.104681, Train_acc: 0.968750 Epoch:0, train_step: 602, loss: 0.092670, Train_acc: 0.968750 Epoch:0, train_step: 603, loss: 0.012407, Train_acc: 1.000000 Epoch:0, train_step: 604, loss: 0.148157, Train_acc: 0.953125 Epoch:0, train_step: 605, loss: 0.149263, Train_acc: 0.953125 Epoch:0, train_step: 606, loss: 0.135360, Train_acc: 0.984375 Epoch:0, train_step: 607, loss: 0.027673, Train_acc: 1.000000 Epoch:0, train_step: 608, loss: 0.064448, Train_acc: 0.984375 Epoch:0, train_step: 609, loss: 0.014802, Train_acc: 1.000000 Epoch:0, train_step: 610, loss: 0.156490, Train_acc: 0.953125 Epoch:0, train_step: 611, loss: 0.003574, Train_acc: 1.000000 Epoch:0, train_step: 612, loss: 0.009171, Train_acc: 1.000000 Epoch:0, train_step: 613, loss: 0.141525, Train_acc: 0.984375 Epoch:0, train_step: 614, loss: 0.091959, Train_acc: 0.968750 Epoch:0, train_step: 615, loss: 0.114826, Train_acc: 0.968750 Epoch:0, train_step: 616, loss: 0.242984, Train_acc: 0.937500 Epoch:0, train_step: 617, loss: 0.184201, Train_acc: 0.953125 Epoch:0, train_step: 618, loss: 0.045102, Train_acc: 0.984375 Epoch:0, train_step: 619, loss: 0.082231, Train_acc: 0.984375 Epoch:0, train_step: 620, loss: 0.157761, Train_acc: 0.968750 Epoch:0, train_step: 621, loss: 0.071581, Train_acc: 0.968750 Epoch:0, train_step: 622, loss: 0.114354, Train_acc: 0.953125 Epoch:0, train_step: 623, loss: 0.078932, Train_acc: 0.984375 Epoch:0, train_step: 624, loss: 0.024570, Train_acc: 0.984375 Epoch:0, train_step: 625, loss: 0.118210, Train_acc: 0.968750 Epoch:0, train_step: 626, loss: 0.070578, Train_acc: 0.968750 Epoch:0, train_step: 627, loss: 0.068049, Train_acc: 0.968750 Epoch:0, train_step: 628, loss: 0.173249, Train_acc: 0.984375 Epoch:0, train_step: 629, loss: 0.053653, Train_acc: 0.968750 Epoch:0, train_step: 630, loss: 0.113527, Train_acc: 0.968750 Epoch:0, train_step: 631, loss: 0.060908, Train_acc: 0.984375 Epoch:0, train_step: 632, loss: 0.129484, Train_acc: 0.984375 Epoch:0, train_step: 633, loss: 0.026330, Train_acc: 1.000000 Epoch:0, train_step: 634, loss: 0.098050, Train_acc: 0.953125 Epoch:0, train_step: 635, loss: 0.045601, Train_acc: 0.984375 Epoch:0, train_step: 636, loss: 0.083090, Train_acc: 0.984375 Epoch:0, train_step: 637, loss: 0.101998, Train_acc: 0.968750 Epoch:0, train_step: 638, loss: 0.079867, Train_acc: 0.984375 Epoch:0, train_step: 639, loss: 0.051505, Train_acc: 0.968750 Epoch:0, train_step: 640, loss: 0.084337, Train_acc: 0.953125 Epoch:0, train_step: 641, loss: 0.127945, Train_acc: 0.968750 Epoch:0, train_step: 642, loss: 0.051788, Train_acc: 0.984375 Epoch:0, train_step: 643, loss: 0.013534, Train_acc: 1.000000 Epoch:0, train_step: 644, loss: 0.070791, Train_acc: 0.968750 Epoch:0, train_step: 645, loss: 0.128107, Train_acc: 0.953125 Epoch:0, train_step: 646, loss: 0.187546, Train_acc: 0.937500 Epoch:0, train_step: 647, loss: 0.216063, Train_acc: 0.968750 Epoch:0, train_step: 648, loss: 0.064086, Train_acc: 0.968750 Epoch:0, train_step: 649, loss: 0.021350, Train_acc: 1.000000 Epoch:0, train_step: 650, loss: 0.048309, Train_acc: 0.984375 Epoch:0, train_step: 651, loss: 0.074624, Train_acc: 0.984375 Epoch:0, train_step: 652, loss: 0.042245, Train_acc: 0.968750 Epoch:0, train_step: 653, loss: 0.097676, Train_acc: 0.968750 Epoch:0, train_step: 654, loss: 0.112774, Train_acc: 0.953125 Epoch:0, train_step: 655, loss: 0.140249, Train_acc: 0.968750 Epoch:0, train_step: 656, loss: 0.046560, Train_acc: 0.984375 Epoch:0, train_step: 657, loss: 0.124764, Train_acc: 0.968750 Epoch:0, train_step: 658, loss: 0.033742, Train_acc: 1.000000 Epoch:0, train_step: 659, loss: 0.047398, Train_acc: 0.984375 Epoch:0, train_step: 660, loss: 0.052990, Train_acc: 0.984375 Epoch:0, train_step: 661, loss: 0.024816, Train_acc: 0.984375 Epoch:0, train_step: 662, loss: 0.069850, Train_acc: 0.984375 Epoch:0, train_step: 663, loss: 0.032616, Train_acc: 1.000000 Epoch:0, train_step: 664, loss: 0.137090, Train_acc: 0.968750 Epoch:0, train_step: 665, loss: 0.052436, Train_acc: 0.968750 Epoch:0, train_step: 666, loss: 0.156463, Train_acc: 0.968750 Epoch:0, train_step: 667, loss: 0.056458, Train_acc: 0.984375 Epoch:0, train_step: 668, loss: 0.047308, Train_acc: 0.984375 Epoch:0, train_step: 669, loss: 0.034602, Train_acc: 1.000000 Epoch:0, train_step: 670, loss: 0.115641, Train_acc: 0.953125 Epoch:0, train_step: 671, loss: 0.075575, Train_acc: 0.984375 Epoch:0, train_step: 672, loss: 0.081296, Train_acc: 0.968750 Epoch:0, train_step: 673, loss: 0.042177, Train_acc: 0.984375 Epoch:0, train_step: 674, loss: 0.133169, Train_acc: 0.968750 Epoch:0, train_step: 675, loss: 0.082916, Train_acc: 0.984375 Epoch:0, train_step: 676, loss: 0.012498, Train_acc: 1.000000 Epoch:0, train_step: 677, loss: 0.006031, Train_acc: 1.000000 Epoch:0, train_step: 678, loss: 0.013714, Train_acc: 1.000000 Epoch:0, train_step: 679, loss: 0.154505, Train_acc: 0.984375 Epoch:0, train_step: 680, loss: 0.047870, Train_acc: 0.984375 Epoch:0, train_step: 681, loss: 0.129738, Train_acc: 0.968750 Epoch:0, train_step: 682, loss: 0.051587, Train_acc: 0.984375 Epoch:0, train_step: 683, loss: 0.168473, Train_acc: 0.968750 Epoch:0, train_step: 684, loss: 0.007952, Train_acc: 1.000000 Epoch:0, train_step: 685, loss: 0.157294, Train_acc: 0.984375 Epoch:0, train_step: 686, loss: 0.091307, Train_acc: 0.968750 Epoch:0, train_step: 687, loss: 0.020595, Train_acc: 1.000000 Epoch:0, train_step: 688, loss: 0.032012, Train_acc: 0.984375 Epoch:0, train_step: 689, loss: 0.054026, Train_acc: 0.968750 Epoch:0, train_step: 690, loss: 0.049512, Train_acc: 0.984375 Epoch:0, train_step: 691, loss: 0.049627, Train_acc: 0.968750 Epoch:0, train_step: 692, loss: 0.097549, Train_acc: 0.984375 Epoch:0, train_step: 693, loss: 0.053732, Train_acc: 0.984375 Epoch:0, train_step: 694, loss: 0.127156, Train_acc: 0.984375 Epoch:0, train_step: 695, loss: 0.177067, Train_acc: 0.953125 Epoch:0, train_step: 696, loss: 0.025097, Train_acc: 0.984375 Epoch:0, train_step: 697, loss: 0.020811, Train_acc: 0.984375 Epoch:0, train_step: 698, loss: 0.014001, Train_acc: 1.000000 Epoch:0, train_step: 699, loss: 0.047914, Train_acc: 0.968750 Epoch:0, train_step: 700, loss: 0.097331, Train_acc: 0.984375 Epoch:0, train_step: 701, loss: 0.170665, Train_acc: 0.968750 Epoch:0, train_step: 702, loss: 0.100533, Train_acc: 0.953125 Epoch:0, train_step: 703, loss: 0.044218, Train_acc: 0.984375 Epoch:0, train_step: 704, loss: 0.043261, Train_acc: 0.984375 Epoch:0, train_step: 705, loss: 0.062660, Train_acc: 0.968750 Epoch:0, train_step: 706, loss: 0.093935, Train_acc: 0.984375 Epoch:0, train_step: 707, loss: 0.005544, Train_acc: 1.000000 Epoch:0, train_step: 708, loss: 0.013894, Train_acc: 1.000000 Epoch:0, train_step: 709, loss: 0.121796, Train_acc: 0.968750 Epoch:0, train_step: 710, loss: 0.100359, Train_acc: 0.968750 Epoch:0, train_step: 711, loss: 0.049521, Train_acc: 0.984375 Epoch:0, train_step: 712, loss: 0.069235, Train_acc: 0.968750 Epoch:0, train_step: 713, loss: 0.218837, Train_acc: 0.921875 Epoch:0, train_step: 714, loss: 0.086587, Train_acc: 0.953125 Epoch:0, train_step: 715, loss: 0.033695, Train_acc: 0.984375 Epoch:0, train_step: 716, loss: 0.072746, Train_acc: 0.984375 Epoch:0, train_step: 717, loss: 0.143899, Train_acc: 0.984375 Epoch:0, train_step: 718, loss: 0.062737, Train_acc: 0.984375 Epoch:0, train_step: 719, loss: 0.111407, Train_acc: 0.953125 Epoch:0, train_step: 720, loss: 0.094527, Train_acc: 0.968750 Epoch:0, train_step: 721, loss: 0.085720, Train_acc: 0.968750 Epoch:0, train_step: 722, loss: 0.024454, Train_acc: 1.000000 Epoch:0, train_step: 723, loss: 0.146350, Train_acc: 0.937500 Epoch:0, train_step: 724, loss: 0.109949, Train_acc: 0.937500 Epoch:0, train_step: 725, loss: 0.109483, Train_acc: 0.968750 Epoch:0, train_step: 726, loss: 0.044225, Train_acc: 1.000000 Epoch:0, train_step: 727, loss: 0.014365, Train_acc: 1.000000 Epoch:0, train_step: 728, loss: 0.023129, Train_acc: 1.000000 Epoch:0, train_step: 729, loss: 0.042722, Train_acc: 0.984375 Epoch:0, train_step: 730, loss: 0.145540, Train_acc: 0.968750 Epoch:0, train_step: 731, loss: 0.198395, Train_acc: 0.921875 Epoch:0, train_step: 732, loss: 0.064631, Train_acc: 0.984375 Epoch:0, train_step: 733, loss: 0.099508, Train_acc: 0.984375 Epoch:0, train_step: 734, loss: 0.072273, Train_acc: 0.984375 Epoch:0, train_step: 735, loss: 0.170864, Train_acc: 0.953125 Epoch:0, train_step: 736, loss: 0.077009, Train_acc: 0.968750 Epoch:0, train_step: 737, loss: 0.112329, Train_acc: 0.968750 Epoch:0, train_step: 738, loss: 0.033545, Train_acc: 1.000000 Epoch:0, train_step: 739, loss: 0.186960, Train_acc: 0.906250 Epoch:0, train_step: 740, loss: 0.087141, Train_acc: 0.968750 Epoch:0, train_step: 741, loss: 0.079029, Train_acc: 0.984375 Epoch:0, train_step: 742, loss: 0.196388, Train_acc: 0.921875 Epoch:0, train_step: 743, loss: 0.162938, Train_acc: 0.953125 Epoch:0, train_step: 744, loss: 0.167673, Train_acc: 0.953125 Epoch:0, train_step: 745, loss: 0.071389, Train_acc: 0.984375 Epoch:0, train_step: 746, loss: 0.215872, Train_acc: 0.953125 Epoch:0, train_step: 747, loss: 0.133365, Train_acc: 0.984375 Epoch:0, train_step: 748, loss: 0.073295, Train_acc: 0.968750 Epoch:0, train_step: 749, loss: 0.054680, Train_acc: 0.984375 Epoch:0, train_step: 750, loss: 0.032706, Train_acc: 1.000000 Epoch:0, train_step: 751, loss: 0.023893, Train_acc: 1.000000 Epoch:0, train_step: 752, loss: 0.172786, Train_acc: 0.937500 Epoch:0, train_step: 753, loss: 0.029887, Train_acc: 0.984375 Epoch:0, train_step: 754, loss: 0.044015, Train_acc: 0.984375 Epoch:0, train_step: 755, loss: 0.042525, Train_acc: 0.984375 Epoch:0, train_step: 756, loss: 0.145952, Train_acc: 0.953125 Epoch:0, train_step: 757, loss: 0.030610, Train_acc: 0.984375 Epoch:0, train_step: 758, loss: 0.062735, Train_acc: 0.953125 Epoch:0, train_step: 759, loss: 0.036648, Train_acc: 0.968750 Epoch:0, train_step: 760, loss: 0.040884, Train_acc: 0.984375 Epoch:0, train_step: 761, loss: 0.112514, Train_acc: 0.937500 Epoch:0, train_step: 762, loss: 0.017300, Train_acc: 1.000000 Epoch:0, train_step: 763, loss: 0.029649, Train_acc: 1.000000 Epoch:0, train_step: 764, loss: 0.042568, Train_acc: 0.984375 Epoch:0, train_step: 765, loss: 0.259343, Train_acc: 0.906250 Epoch:0, train_step: 766, loss: 0.342446, Train_acc: 0.875000 Epoch:0, train_step: 767, loss: 0.164576, Train_acc: 0.937500 Epoch:0, train_step: 768, loss: 0.063113, Train_acc: 0.968750 Epoch:0, train_step: 769, loss: 0.230128, Train_acc: 0.937500 Epoch:0, train_step: 770, loss: 0.074594, Train_acc: 0.984375 Epoch:0, train_step: 771, loss: 0.004516, Train_acc: 1.000000 Epoch:0, train_step: 772, loss: 0.040575, Train_acc: 0.984375 Epoch:0, train_step: 773, loss: 0.200137, Train_acc: 0.937500 Epoch:0, train_step: 774, loss: 0.189405, Train_acc: 0.953125 Epoch:0, train_step: 775, loss: 0.198560, Train_acc: 0.953125 Epoch:0, train_step: 776, loss: 0.052576, Train_acc: 0.984375 Epoch:0, train_step: 777, loss: 0.030567, Train_acc: 1.000000 Epoch:0, train_step: 778, loss: 0.046630, Train_acc: 0.984375 Epoch:0, train_step: 779, loss: 0.078412, Train_acc: 0.968750 Epoch:0, train_step: 780, loss: 0.138941, Train_acc: 0.953125 Epoch:0, train_step: 781, loss: 0.043254, Train_acc: 0.984375 Epoch:0, train_step: 782, loss: 0.016494, Train_acc: 1.000000 Epoch:0, train_step: 783, loss: 0.052462, Train_acc: 0.968750 Epoch:0, train_step: 784, loss: 0.025032, Train_acc: 1.000000 Epoch:0, train_step: 785, loss: 0.121941, Train_acc: 0.953125 Epoch:0, train_step: 786, loss: 0.019391, Train_acc: 1.000000 Epoch:0, train_step: 787, loss: 0.091195, Train_acc: 0.968750 Epoch:0, train_step: 788, loss: 0.123239, Train_acc: 0.968750 Epoch:0, train_step: 789, loss: 0.084936, Train_acc: 0.984375 Epoch:0, train_step: 790, loss: 0.117241, Train_acc: 0.968750 Epoch:0, train_step: 791, loss: 0.058392, Train_acc: 0.968750 Epoch:0, train_step: 792, loss: 0.004403, Train_acc: 1.000000 Epoch:0, train_step: 793, loss: 0.086076, Train_acc: 0.984375 Epoch:0, train_step: 794, loss: 0.016932, Train_acc: 1.000000 Epoch:0, train_step: 795, loss: 0.037173, Train_acc: 0.984375 Epoch:0, train_step: 796, loss: 0.100409, Train_acc: 0.968750 Epoch:0, train_step: 797, loss: 0.154528, Train_acc: 0.937500 Epoch:0, train_step: 798, loss: 0.017132, Train_acc: 1.000000 Epoch:0, train_step: 799, loss: 0.005891, Train_acc: 1.000000 Epoch:0, train_step: 800, loss: 0.062366, Train_acc: 0.984375 Epoch:0, train_step: 801, loss: 0.085021, Train_acc: 0.968750 Epoch:0, train_step: 802, loss: 0.053436, Train_acc: 0.968750 Epoch:0, 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train_step: 915, loss: 0.007488, Train_acc: 1.000000 Epoch:0, train_step: 916, loss: 0.003170, Train_acc: 1.000000 Epoch:0, train_step: 917, loss: 0.034512, Train_acc: 0.968750 Epoch:0, train_step: 918, loss: 0.000769, Train_acc: 1.000000 Epoch:0, train_step: 919, loss: 0.098379, Train_acc: 0.984375 Epoch:0, train_step: 920, loss: 0.100509, Train_acc: 0.984375 Epoch:0, train_step: 921, loss: 0.002132, Train_acc: 1.000000 Epoch:0, train_step: 922, loss: 0.000917, Train_acc: 1.000000 Epoch:0, train_step: 923, loss: 0.004179, Train_acc: 1.000000 Epoch:0, train_step: 924, loss: 0.001335, Train_acc: 1.000000 Epoch:0, train_step: 925, loss: 0.001218, Train_acc: 1.000000 Epoch:0, train_step: 926, loss: 0.001507, Train_acc: 1.000000 Epoch:0, train_step: 927, loss: 0.036220, Train_acc: 0.984375 Epoch:0, train_step: 928, loss: 0.031104, Train_acc: 0.984375 Epoch:0, train_step: 929, loss: 0.007464, Train_acc: 1.000000 Epoch:0, train_step: 930, loss: 0.002622, Train_acc: 1.000000 Epoch:0, train_step: 931, loss: 0.001638, Train_acc: 1.000000 Epoch:0, train_step: 932, loss: 0.003810, Train_acc: 1.000000 Epoch:0, train_step: 933, loss: 0.142454, Train_acc: 0.968750 Epoch:0, train_step: 934, loss: 0.360559, Train_acc: 0.921875 Epoch:0, train_step: 935, loss: 0.035951, Train_acc: 0.984375 Epoch:0, train_step: 936, loss: 0.002807, Train_acc: 1.000000 Epoch:0, train_step: 937, loss: 0.222062, Train_acc: 0.984375 Epoch:0, avg_train_loss: 0.132467, avg_train_acc: 0.959495, Test_acc: 0.981370 Epoch:1, train_step: 938, loss: 0.024458, Train_acc: 0.984375 Epoch:1, train_step: 939, loss: 0.090091, Train_acc: 0.968750 Epoch:1, train_step: 940, loss: 0.335877, Train_acc: 0.921875 Epoch:1, train_step: 941, loss: 0.056512, Train_acc: 0.984375 Epoch:1, train_step: 942, loss: 0.026927, Train_acc: 0.984375 Epoch:1, train_step: 943, loss: 0.006757, Train_acc: 1.000000 Epoch:1, train_step: 944, loss: 0.049244, Train_acc: 0.968750 Epoch:1, train_step: 945, loss: 0.197179, Train_acc: 0.968750 Epoch:1, train_step: 946, loss: 0.015287, Train_acc: 1.000000 Epoch:1, train_step: 947, loss: 0.203276, Train_acc: 0.953125 Epoch:1, train_step: 948, loss: 0.028431, Train_acc: 0.984375 Epoch:1, train_step: 949, loss: 0.080308, Train_acc: 0.984375 Epoch:1, train_step: 950, loss: 0.076476, Train_acc: 0.968750 Epoch:1, train_step: 951, loss: 0.107651, Train_acc: 0.968750 Epoch:1, train_step: 952, loss: 0.184043, Train_acc: 0.968750 Epoch:1, train_step: 953, loss: 0.076401, Train_acc: 0.968750 Epoch:1, train_step: 954, loss: 0.115396, Train_acc: 0.953125 Epoch:1, train_step: 955, loss: 0.157918, Train_acc: 0.921875 Epoch:1, train_step: 956, loss: 0.039221, Train_acc: 0.984375 Epoch:1, train_step: 957, loss: 0.085195, Train_acc: 0.968750 Epoch:1, train_step: 958, loss: 0.084867, Train_acc: 0.968750 Epoch:1, train_step: 959, loss: 0.134926, Train_acc: 0.953125 Epoch:1, train_step: 960, loss: 0.005242, Train_acc: 1.000000 Epoch:1, train_step: 961, loss: 0.068374, Train_acc: 0.984375 Epoch:1, train_step: 962, loss: 0.060103, Train_acc: 0.984375 Epoch:1, train_step: 963, loss: 0.201356, Train_acc: 0.953125 Epoch:1, train_step: 964, loss: 0.053252, Train_acc: 0.984375 Epoch:1, train_step: 965, loss: 0.079910, Train_acc: 0.968750 Epoch:1, train_step: 966, loss: 0.016053, Train_acc: 1.000000 Epoch:1, train_step: 967, loss: 0.016077, Train_acc: 1.000000 Epoch:1, train_step: 968, loss: 0.110585, Train_acc: 0.968750 Epoch:1, train_step: 969, loss: 0.046955, Train_acc: 0.968750 Epoch:1, train_step: 970, loss: 0.041192, Train_acc: 0.968750 Epoch:1, train_step: 971, loss: 0.077525, Train_acc: 0.984375 Epoch:1, train_step: 972, loss: 0.041719, Train_acc: 0.984375 Epoch:1, train_step: 973, loss: 0.034905, Train_acc: 0.984375 Epoch:1, train_step: 974, loss: 0.005043, Train_acc: 1.000000 Epoch:1, train_step: 975, loss: 0.077613, Train_acc: 0.984375 Epoch:1, train_step: 976, loss: 0.036764, Train_acc: 0.968750 Epoch:1, train_step: 977, loss: 0.050239, Train_acc: 0.968750 Epoch:1, train_step: 978, loss: 0.085424, Train_acc: 0.984375 Epoch:1, train_step: 979, loss: 0.127186, Train_acc: 0.968750 Epoch:1, train_step: 980, loss: 0.162237, Train_acc: 0.953125 Epoch:1, train_step: 981, loss: 0.009085, Train_acc: 1.000000 Epoch:1, train_step: 982, loss: 0.030395, Train_acc: 1.000000 Epoch:1, train_step: 983, loss: 0.018612, Train_acc: 1.000000 Epoch:1, train_step: 984, loss: 0.011074, Train_acc: 1.000000 Epoch:1, train_step: 985, loss: 0.050869, Train_acc: 0.984375 Epoch:1, train_step: 986, loss: 0.018823, Train_acc: 1.000000 Epoch:1, train_step: 987, loss: 0.002219, Train_acc: 1.000000 Epoch:1, train_step: 988, loss: 0.085333, Train_acc: 0.984375 Epoch:1, train_step: 989, loss: 0.048177, Train_acc: 0.984375 Epoch:1, train_step: 990, loss: 0.010411, Train_acc: 1.000000 Epoch:1, train_step: 991, loss: 0.078645, Train_acc: 0.968750 Epoch:1, train_step: 992, loss: 0.050817, Train_acc: 0.984375 Epoch:1, train_step: 993, loss: 0.012464, Train_acc: 1.000000 Epoch:1, train_step: 994, loss: 0.025207, Train_acc: 0.984375 Epoch:1, train_step: 995, loss: 0.386211, Train_acc: 0.937500 Epoch:1, train_step: 996, loss: 0.044157, Train_acc: 1.000000 Epoch:1, train_step: 997, loss: 0.029231, Train_acc: 0.984375 Epoch:1, train_step: 998, loss: 0.008043, Train_acc: 1.000000 Epoch:1, train_step: 999, loss: 0.036379, Train_acc: 0.984375 Epoch:1, train_step: 1000, loss: 0.135790, Train_acc: 0.953125 Epoch:1, train_step: 1001, loss: 0.026449, Train_acc: 1.000000 Epoch:1, train_step: 1002, loss: 0.065872, Train_acc: 0.984375 Epoch:1, train_step: 1003, loss: 0.018775, Train_acc: 0.984375 Epoch:1, train_step: 1004, loss: 0.034122, Train_acc: 0.984375 Epoch:1, train_step: 1005, loss: 0.032323, Train_acc: 0.984375 Epoch:1, train_step: 1006, loss: 0.020981, Train_acc: 1.000000 Epoch:1, train_step: 1007, loss: 0.164091, Train_acc: 0.953125 Epoch:1, train_step: 1008, loss: 0.016277, Train_acc: 0.984375 Epoch:1, train_step: 1009, loss: 0.022845, Train_acc: 0.984375 Epoch:1, train_step: 1010, loss: 0.082793, Train_acc: 0.984375 Epoch:1, train_step: 1011, loss: 0.032599, Train_acc: 0.984375 Epoch:1, train_step: 1012, loss: 0.036063, Train_acc: 0.984375 Epoch:1, train_step: 1013, loss: 0.015374, Train_acc: 1.000000 Epoch:1, train_step: 1014, loss: 0.008429, Train_acc: 1.000000 Epoch:1, train_step: 1015, loss: 0.067247, Train_acc: 0.968750 Epoch:1, train_step: 1016, loss: 0.041650, Train_acc: 0.984375 Epoch:1, train_step: 1017, loss: 0.041630, Train_acc: 0.984375 Epoch:1, train_step: 1018, loss: 0.023889, Train_acc: 1.000000 Epoch:1, train_step: 1019, loss: 0.018447, Train_acc: 1.000000 Epoch:1, train_step: 1020, loss: 0.169477, Train_acc: 0.968750 Epoch:1, train_step: 1021, loss: 0.071444, Train_acc: 0.968750 Epoch:1, train_step: 1022, loss: 0.034456, Train_acc: 0.984375 Epoch:1, train_step: 1023, loss: 0.072218, Train_acc: 0.984375 Epoch:1, train_step: 1024, loss: 0.073448, Train_acc: 0.968750 Epoch:1, train_step: 1025, loss: 0.014264, Train_acc: 1.000000 Epoch:1, train_step: 1026, loss: 0.046867, Train_acc: 1.000000 Epoch:1, train_step: 1027, loss: 0.095335, Train_acc: 0.937500 Epoch:1, train_step: 1028, loss: 0.104384, Train_acc: 0.968750 Epoch:1, train_step: 1029, loss: 0.038103, Train_acc: 0.984375 Epoch:1, train_step: 1030, loss: 0.137027, Train_acc: 0.984375 Epoch:1, train_step: 1031, loss: 0.056230, Train_acc: 0.984375 Epoch:1, train_step: 1032, loss: 0.026024, Train_acc: 1.000000 Epoch:1, train_step: 1033, loss: 0.127700, Train_acc: 0.984375 Epoch:1, train_step: 1034, loss: 0.014893, Train_acc: 1.000000 Epoch:1, train_step: 1035, loss: 0.145359, Train_acc: 0.968750 Epoch:1, train_step: 1036, loss: 0.015837, Train_acc: 1.000000 Epoch:1, train_step: 1037, loss: 0.013972, Train_acc: 1.000000 Epoch:1, train_step: 1038, loss: 0.131495, Train_acc: 0.968750 Epoch:1, train_step: 1039, loss: 0.033242, Train_acc: 0.984375 Epoch:1, train_step: 1040, loss: 0.005205, Train_acc: 1.000000 Epoch:1, train_step: 1041, loss: 0.018534, Train_acc: 0.984375 Epoch:1, train_step: 1042, loss: 0.115117, Train_acc: 0.937500 Epoch:1, train_step: 1043, loss: 0.007965, Train_acc: 1.000000 Epoch:1, train_step: 1044, loss: 0.142098, Train_acc: 0.968750 Epoch:1, train_step: 1045, loss: 0.231231, Train_acc: 0.953125 Epoch:1, train_step: 1046, loss: 0.151597, Train_acc: 0.921875 Epoch:1, train_step: 1047, loss: 0.185358, Train_acc: 0.953125 Epoch:1, train_step: 1048, loss: 0.041049, Train_acc: 0.984375 Epoch:1, train_step: 1049, loss: 0.005625, Train_acc: 1.000000 Epoch:1, train_step: 1050, loss: 0.054028, Train_acc: 0.968750 Epoch:1, train_step: 1051, loss: 0.349905, Train_acc: 0.953125 Epoch:1, train_step: 1052, loss: 0.092818, Train_acc: 0.953125 Epoch:1, train_step: 1053, loss: 0.023645, Train_acc: 1.000000 Epoch:1, train_step: 1054, loss: 0.008072, Train_acc: 1.000000 Epoch:1, train_step: 1055, loss: 0.065541, Train_acc: 0.968750 Epoch:1, train_step: 1056, loss: 0.219798, Train_acc: 0.937500 Epoch:1, train_step: 1057, loss: 0.113375, Train_acc: 0.984375 Epoch:1, train_step: 1058, loss: 0.059414, Train_acc: 0.984375 Epoch:1, train_step: 1059, loss: 0.070043, Train_acc: 0.968750 Epoch:1, train_step: 1060, loss: 0.063710, Train_acc: 0.968750 Epoch:1, train_step: 1061, loss: 0.066200, Train_acc: 0.968750 Epoch:1, train_step: 1062, loss: 0.094509, Train_acc: 0.968750 Epoch:1, train_step: 1063, loss: 0.074021, Train_acc: 0.968750 Epoch:1, train_step: 1064, loss: 0.072358, Train_acc: 0.968750 Epoch:1, train_step: 1065, loss: 0.015203, Train_acc: 1.000000 Epoch:1, train_step: 1066, loss: 0.112173, Train_acc: 0.968750 Epoch:1, train_step: 1067, loss: 0.027910, Train_acc: 1.000000 Epoch:1, train_step: 1068, loss: 0.023895, Train_acc: 0.984375 Epoch:1, train_step: 1069, loss: 0.041531, Train_acc: 0.984375 Epoch:1, train_step: 1070, loss: 0.024782, Train_acc: 1.000000 Epoch:1, train_step: 1071, loss: 0.006455, Train_acc: 1.000000 Epoch:1, train_step: 1072, loss: 0.045976, Train_acc: 0.984375 Epoch:1, train_step: 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Epoch:1, train_step: 1105, loss: 0.044439, Train_acc: 0.984375 Epoch:1, train_step: 1106, loss: 0.093211, Train_acc: 0.968750 Epoch:1, train_step: 1107, loss: 0.066874, Train_acc: 0.984375 Epoch:1, train_step: 1108, loss: 0.004870, Train_acc: 1.000000 Epoch:1, train_step: 1109, loss: 0.151611, Train_acc: 0.984375 Epoch:1, train_step: 1110, loss: 0.070847, Train_acc: 0.984375 Epoch:1, train_step: 1111, loss: 0.008016, Train_acc: 1.000000 Epoch:1, train_step: 1112, loss: 0.017392, Train_acc: 1.000000 Epoch:1, train_step: 1113, loss: 0.099816, Train_acc: 0.984375 Epoch:1, train_step: 1114, loss: 0.006178, Train_acc: 1.000000 Epoch:1, train_step: 1115, loss: 0.058641, Train_acc: 0.968750 Epoch:1, train_step: 1116, loss: 0.027263, Train_acc: 1.000000 Epoch:1, train_step: 1117, loss: 0.007737, Train_acc: 1.000000 Epoch:1, train_step: 1118, loss: 0.038707, Train_acc: 0.984375 Epoch:1, train_step: 1119, loss: 0.064119, Train_acc: 0.968750 Epoch:1, train_step: 1120, loss: 0.048803, Train_acc: 0.984375 Epoch:1, train_step: 1121, loss: 0.042083, Train_acc: 0.984375 Epoch:1, train_step: 1122, loss: 0.087864, Train_acc: 0.968750 Epoch:1, train_step: 1123, loss: 0.066050, Train_acc: 0.984375 Epoch:1, train_step: 1124, loss: 0.059803, Train_acc: 0.984375 Epoch:1, train_step: 1125, loss: 0.030146, Train_acc: 0.984375 Epoch:1, train_step: 1126, loss: 0.039315, Train_acc: 0.968750 Epoch:1, train_step: 1127, loss: 0.011188, Train_acc: 1.000000 Epoch:1, train_step: 1128, loss: 0.023380, Train_acc: 1.000000 Epoch:1, train_step: 1129, loss: 0.033743, Train_acc: 1.000000 Epoch:1, train_step: 1130, loss: 0.026096, Train_acc: 1.000000 Epoch:1, train_step: 1131, loss: 0.072585, Train_acc: 0.984375 Epoch:1, train_step: 1132, loss: 0.011966, Train_acc: 1.000000 Epoch:1, train_step: 1133, loss: 0.003902, Train_acc: 1.000000 Epoch:1, train_step: 1134, loss: 0.128676, Train_acc: 0.984375 Epoch:1, train_step: 1135, loss: 0.058537, Train_acc: 0.968750 Epoch:1, train_step: 1136, loss: 0.014401, Train_acc: 0.984375 Epoch:1, train_step: 1137, loss: 0.018721, Train_acc: 1.000000 Epoch:1, train_step: 1138, loss: 0.058503, Train_acc: 0.968750 Epoch:1, train_step: 1139, loss: 0.069145, Train_acc: 0.968750 Epoch:1, train_step: 1140, loss: 0.146337, Train_acc: 0.953125 Epoch:1, train_step: 1141, loss: 0.029720, Train_acc: 0.984375 Epoch:1, train_step: 1142, loss: 0.067957, Train_acc: 0.984375 Epoch:1, train_step: 1143, loss: 0.064355, Train_acc: 0.953125 Epoch:1, train_step: 1144, loss: 0.030848, Train_acc: 1.000000 Epoch:1, train_step: 1145, loss: 0.101633, Train_acc: 0.968750 Epoch:1, train_step: 1146, loss: 0.017026, Train_acc: 1.000000 Epoch:1, train_step: 1147, loss: 0.099059, Train_acc: 0.937500 Epoch:1, train_step: 1148, loss: 0.008654, Train_acc: 1.000000 Epoch:1, train_step: 1149, loss: 0.035193, Train_acc: 0.984375 Epoch:1, train_step: 1150, loss: 0.050496, Train_acc: 0.984375 Epoch:1, train_step: 1151, loss: 0.076204, Train_acc: 0.984375 Epoch:1, train_step: 1152, loss: 0.062650, Train_acc: 0.984375 Epoch:1, train_step: 1153, loss: 0.016155, Train_acc: 1.000000 Epoch:1, train_step: 1154, loss: 0.146432, Train_acc: 0.968750 Epoch:1, train_step: 1155, loss: 0.075510, Train_acc: 0.953125 Epoch:1, train_step: 1156, loss: 0.077120, Train_acc: 0.968750 Epoch:1, train_step: 1157, loss: 0.054073, Train_acc: 0.984375 Epoch:1, train_step: 1158, loss: 0.007932, Train_acc: 1.000000 Epoch:1, train_step: 1159, loss: 0.047653, Train_acc: 0.984375 Epoch:1, train_step: 1160, loss: 0.085088, Train_acc: 0.984375 Epoch:1, train_step: 1161, loss: 0.009743, Train_acc: 1.000000 Epoch:1, train_step: 1162, loss: 0.081701, Train_acc: 0.968750 Epoch:1, train_step: 1163, loss: 0.016401, Train_acc: 0.984375 Epoch:1, train_step: 1164, loss: 0.020277, Train_acc: 1.000000 Epoch:1, train_step: 1165, loss: 0.157947, Train_acc: 0.968750 Epoch:1, train_step: 1166, loss: 0.005295, Train_acc: 1.000000 Epoch:1, train_step: 1167, loss: 0.044329, Train_acc: 0.984375 Epoch:1, train_step: 1168, loss: 0.053279, Train_acc: 1.000000 Epoch:1, train_step: 1169, loss: 0.040873, Train_acc: 0.984375 Epoch:1, train_step: 1170, loss: 0.004482, Train_acc: 1.000000 Epoch:1, train_step: 1171, loss: 0.028684, Train_acc: 1.000000 Epoch:1, train_step: 1172, loss: 0.001679, Train_acc: 1.000000 Epoch:1, train_step: 1173, loss: 0.074401, Train_acc: 0.968750 Epoch:1, train_step: 1174, loss: 0.014926, Train_acc: 1.000000 Epoch:1, train_step: 1175, loss: 0.037094, Train_acc: 0.984375 Epoch:1, train_step: 1176, loss: 0.032334, Train_acc: 0.984375 Epoch:1, train_step: 1177, loss: 0.063971, Train_acc: 0.984375 Epoch:1, train_step: 1178, loss: 0.017000, Train_acc: 1.000000 Epoch:1, train_step: 1179, loss: 0.037079, Train_acc: 0.984375 Epoch:1, train_step: 1180, loss: 0.013289, Train_acc: 1.000000 Epoch:1, train_step: 1181, loss: 0.032559, Train_acc: 0.984375 Epoch:1, train_step: 1182, loss: 0.011366, Train_acc: 1.000000 Epoch:1, train_step: 1183, loss: 0.030907, Train_acc: 0.984375 Epoch:1, train_step: 1184, loss: 0.078756, Train_acc: 0.968750 Epoch:1, train_step: 1185, loss: 0.009226, Train_acc: 1.000000 Epoch:1, train_step: 1186, loss: 0.048243, Train_acc: 0.984375 Epoch:1, train_step: 1187, loss: 0.080891, Train_acc: 0.968750 Epoch:1, train_step: 1188, loss: 0.059754, Train_acc: 0.968750 Epoch:1, train_step: 1189, loss: 0.019055, Train_acc: 1.000000 Epoch:1, train_step: 1190, loss: 0.025502, Train_acc: 0.984375 Epoch:1, train_step: 1191, loss: 0.029505, Train_acc: 0.984375 Epoch:1, train_step: 1192, loss: 0.014363, Train_acc: 1.000000 Epoch:1, train_step: 1193, loss: 0.035822, Train_acc: 0.984375 Epoch:1, train_step: 1194, loss: 0.009090, Train_acc: 1.000000 Epoch:1, train_step: 1195, loss: 0.057400, Train_acc: 0.984375 Epoch:1, train_step: 1196, loss: 0.055539, Train_acc: 0.984375 Epoch:1, train_step: 1197, loss: 0.013807, Train_acc: 1.000000 Epoch:1, train_step: 1198, loss: 0.107312, Train_acc: 0.953125 Epoch:1, train_step: 1199, loss: 0.068503, Train_acc: 0.968750 Epoch:1, train_step: 1200, loss: 0.018770, Train_acc: 1.000000 Epoch:1, train_step: 1201, loss: 0.021386, Train_acc: 1.000000 Epoch:1, train_step: 1202, loss: 0.014222, Train_acc: 1.000000 Epoch:1, train_step: 1203, loss: 0.101056, Train_acc: 0.968750 Epoch:1, train_step: 1204, loss: 0.066270, Train_acc: 0.968750 Epoch:1, train_step: 1205, loss: 0.037115, Train_acc: 0.984375 Epoch:1, train_step: 1206, loss: 0.050390, Train_acc: 0.968750 Epoch:1, train_step: 1207, loss: 0.056551, Train_acc: 0.968750 Epoch:1, train_step: 1208, loss: 0.013353, Train_acc: 1.000000 Epoch:1, train_step: 1209, loss: 0.014125, Train_acc: 1.000000 Epoch:1, train_step: 1210, loss: 0.044821, Train_acc: 0.968750 Epoch:1, train_step: 1211, loss: 0.017359, Train_acc: 1.000000 Epoch:1, train_step: 1212, loss: 0.262172, Train_acc: 0.890625 Epoch:1, train_step: 1213, loss: 0.078255, Train_acc: 0.953125 Epoch:1, train_step: 1214, loss: 0.092419, Train_acc: 0.968750 Epoch:1, train_step: 1215, loss: 0.048925, Train_acc: 0.984375 Epoch:1, train_step: 1216, loss: 0.114024, Train_acc: 0.953125 Epoch:1, train_step: 1217, loss: 0.035194, Train_acc: 0.984375 Epoch:1, train_step: 1218, loss: 0.059348, Train_acc: 0.968750 Epoch:1, train_step: 1219, loss: 0.051514, Train_acc: 0.984375 Epoch:1, train_step: 1220, loss: 0.028673, Train_acc: 0.984375 Epoch:1, train_step: 1221, loss: 0.080612, Train_acc: 0.968750 Epoch:1, train_step: 1222, loss: 0.036244, Train_acc: 0.984375 Epoch:1, train_step: 1223, loss: 0.052717, Train_acc: 0.984375 Epoch:1, train_step: 1224, loss: 0.075998, Train_acc: 0.984375 Epoch:1, train_step: 1225, loss: 0.057143, Train_acc: 0.968750 Epoch:1, train_step: 1226, loss: 0.009111, Train_acc: 1.000000 Epoch:1, train_step: 1227, loss: 0.016371, Train_acc: 1.000000 Epoch:1, train_step: 1228, loss: 0.028061, Train_acc: 0.984375 Epoch:1, train_step: 1229, loss: 0.009978, Train_acc: 1.000000 Epoch:1, train_step: 1230, loss: 0.034096, Train_acc: 0.984375 Epoch:1, train_step: 1231, loss: 0.008584, Train_acc: 1.000000 Epoch:1, train_step: 1232, loss: 0.044234, Train_acc: 0.984375 Epoch:1, train_step: 1233, loss: 0.003198, Train_acc: 1.000000 Epoch:1, train_step: 1234, loss: 0.003362, Train_acc: 1.000000 Epoch:1, train_step: 1235, loss: 0.020356, Train_acc: 0.984375 Epoch:1, train_step: 1236, loss: 0.055592, Train_acc: 0.984375 Epoch:1, train_step: 1237, loss: 0.019110, Train_acc: 1.000000 Epoch:1, train_step: 1238, loss: 0.098953, Train_acc: 0.984375 Epoch:1, train_step: 1239, loss: 0.012718, Train_acc: 1.000000 Epoch:1, train_step: 1240, loss: 0.135840, Train_acc: 0.953125 Epoch:1, train_step: 1241, loss: 0.027289, Train_acc: 1.000000 Epoch:1, train_step: 1242, loss: 0.045244, Train_acc: 0.984375 Epoch:1, train_step: 1243, loss: 0.062528, Train_acc: 0.968750 Epoch:1, train_step: 1244, loss: 0.022882, Train_acc: 1.000000 Epoch:1, train_step: 1245, loss: 0.001886, Train_acc: 1.000000 Epoch:1, train_step: 1246, loss: 0.018068, Train_acc: 1.000000 Epoch:1, train_step: 1247, loss: 0.012125, Train_acc: 1.000000 Epoch:1, train_step: 1248, loss: 0.109994, Train_acc: 0.953125 Epoch:1, train_step: 1249, loss: 0.020109, Train_acc: 0.984375 Epoch:1, train_step: 1250, loss: 0.023441, Train_acc: 0.984375 Epoch:1, train_step: 1251, loss: 0.089921, Train_acc: 0.984375 Epoch:1, train_step: 1252, loss: 0.020505, Train_acc: 0.984375 Epoch:1, train_step: 1253, loss: 0.035054, Train_acc: 0.984375 Epoch:1, train_step: 1254, loss: 0.031285, Train_acc: 0.984375 Epoch:1, train_step: 1255, loss: 0.018398, Train_acc: 0.984375 Epoch:1, train_step: 1256, loss: 0.004549, Train_acc: 1.000000 Epoch:1, train_step: 1257, loss: 0.015583, Train_acc: 1.000000 Epoch:1, train_step: 1258, loss: 0.010700, Train_acc: 1.000000 Epoch:1, train_step: 1259, loss: 0.110764, Train_acc: 0.984375 Epoch:1, train_step: 1260, loss: 0.111554, Train_acc: 0.953125 Epoch:1, train_step: 1261, loss: 0.056107, Train_acc: 0.984375 Epoch:1, train_step: 1262, loss: 0.181742, Train_acc: 0.968750 Epoch:1, train_step: 1263, loss: 0.023209, Train_acc: 1.000000 Epoch:1, train_step: 1264, loss: 0.010164, Train_acc: 1.000000 Epoch:1, train_step: 1265, loss: 0.011554, Train_acc: 1.000000 Epoch:1, train_step: 1266, loss: 0.019112, Train_acc: 1.000000 Epoch:1, train_step: 1267, loss: 0.002210, Train_acc: 1.000000 Epoch:1, train_step: 1268, loss: 0.083014, Train_acc: 0.968750 Epoch:1, train_step: 1269, loss: 0.019894, Train_acc: 1.000000 Epoch:1, train_step: 1270, loss: 0.012304, Train_acc: 1.000000 Epoch:1, train_step: 1271, loss: 0.062113, Train_acc: 0.984375 Epoch:1, train_step: 1272, loss: 0.014762, Train_acc: 1.000000 Epoch:1, train_step: 1273, loss: 0.056098, Train_acc: 0.984375 Epoch:1, train_step: 1274, loss: 0.060482, Train_acc: 0.984375 Epoch:1, train_step: 1275, loss: 0.039415, Train_acc: 0.968750 Epoch:1, train_step: 1276, loss: 0.065834, Train_acc: 0.984375 Epoch:1, train_step: 1277, loss: 0.012265, Train_acc: 1.000000 Epoch:1, train_step: 1278, loss: 0.017959, Train_acc: 1.000000 Epoch:1, train_step: 1279, loss: 0.013812, Train_acc: 1.000000 Epoch:1, train_step: 1280, loss: 0.034347, Train_acc: 0.984375 Epoch:1, train_step: 1281, loss: 0.017238, Train_acc: 1.000000 Epoch:1, train_step: 1282, loss: 0.015800, Train_acc: 1.000000 Epoch:1, train_step: 1283, loss: 0.021695, Train_acc: 0.984375 Epoch:1, train_step: 1284, loss: 0.014953, Train_acc: 1.000000 Epoch:1, train_step: 1285, loss: 0.093228, Train_acc: 0.968750 Epoch:1, train_step: 1286, loss: 0.078686, Train_acc: 0.984375 Epoch:1, train_step: 1287, loss: 0.035793, Train_acc: 0.984375 Epoch:1, train_step: 1288, loss: 0.027417, Train_acc: 1.000000 Epoch:1, train_step: 1289, loss: 0.055598, Train_acc: 0.984375 Epoch:1, train_step: 1290, loss: 0.055271, Train_acc: 0.984375 Epoch:1, train_step: 1291, loss: 0.042512, Train_acc: 0.984375 Epoch:1, train_step: 1292, loss: 0.027687, Train_acc: 0.984375 Epoch:1, train_step: 1293, loss: 0.026340, Train_acc: 0.984375 Epoch:1, train_step: 1294, loss: 0.017280, Train_acc: 1.000000 Epoch:1, train_step: 1295, loss: 0.018775, Train_acc: 0.984375 Epoch:1, train_step: 1296, loss: 0.001126, Train_acc: 1.000000 Epoch:1, train_step: 1297, loss: 0.017033, Train_acc: 1.000000 Epoch:1, train_step: 1298, loss: 0.052610, Train_acc: 0.984375 Epoch:1, train_step: 1299, loss: 0.069684, Train_acc: 0.984375 Epoch:1, train_step: 1300, loss: 0.015136, Train_acc: 1.000000 Epoch:1, train_step: 1301, loss: 0.006063, Train_acc: 1.000000 Epoch:1, train_step: 1302, loss: 0.001587, Train_acc: 1.000000 Epoch:1, train_step: 1303, loss: 0.019075, Train_acc: 1.000000 Epoch:1, train_step: 1304, loss: 0.019589, Train_acc: 0.984375 Epoch:1, train_step: 1305, loss: 0.019559, Train_acc: 0.984375 Epoch:1, train_step: 1306, loss: 0.053443, Train_acc: 0.984375 Epoch:1, train_step: 1307, loss: 0.035118, Train_acc: 0.984375 Epoch:1, train_step: 1308, loss: 0.066954, Train_acc: 0.984375 Epoch:1, train_step: 1309, loss: 0.006525, Train_acc: 1.000000 Epoch:1, train_step: 1310, loss: 0.137878, Train_acc: 0.968750 Epoch:1, train_step: 1311, loss: 0.138816, Train_acc: 0.968750 Epoch:1, train_step: 1312, loss: 0.021923, Train_acc: 1.000000 Epoch:1, train_step: 1313, loss: 0.007277, Train_acc: 1.000000 Epoch:1, train_step: 1314, loss: 0.072857, Train_acc: 0.968750 Epoch:1, train_step: 1315, loss: 0.014837, Train_acc: 1.000000 Epoch:1, train_step: 1316, loss: 0.039814, Train_acc: 0.984375 Epoch:1, train_step: 1317, loss: 0.026886, Train_acc: 1.000000 Epoch:1, train_step: 1318, loss: 0.001524, Train_acc: 1.000000 Epoch:1, train_step: 1319, loss: 0.005638, Train_acc: 1.000000 Epoch:1, train_step: 1320, loss: 0.012605, Train_acc: 1.000000 Epoch:1, train_step: 1321, loss: 0.016840, Train_acc: 1.000000 Epoch:1, train_step: 1322, loss: 0.032871, Train_acc: 1.000000 Epoch:1, train_step: 1323, loss: 0.042037, Train_acc: 0.984375 Epoch:1, train_step: 1324, loss: 0.009339, Train_acc: 1.000000 Epoch:1, train_step: 1325, loss: 0.102141, Train_acc: 0.984375 Epoch:1, train_step: 1326, loss: 0.015333, Train_acc: 0.984375 Epoch:1, train_step: 1327, loss: 0.021546, Train_acc: 1.000000 Epoch:1, train_step: 1328, loss: 0.009968, Train_acc: 1.000000 Epoch:1, train_step: 1329, loss: 0.048094, Train_acc: 0.968750 Epoch:1, train_step: 1330, loss: 0.053697, Train_acc: 0.984375 Epoch:1, train_step: 1331, loss: 0.060101, Train_acc: 0.984375 Epoch:1, train_step: 1332, loss: 0.023153, Train_acc: 0.984375 Epoch:1, train_step: 1333, loss: 0.010755, Train_acc: 1.000000 Epoch:1, train_step: 1334, loss: 0.004665, Train_acc: 1.000000 Epoch:1, train_step: 1335, loss: 0.002855, Train_acc: 1.000000 Epoch:1, train_step: 1336, loss: 0.026864, Train_acc: 0.984375 Epoch:1, train_step: 1337, loss: 0.077771, Train_acc: 0.968750 Epoch:1, train_step: 1338, loss: 0.029491, Train_acc: 0.984375 Epoch:1, train_step: 1339, loss: 0.105920, Train_acc: 0.984375 Epoch:1, train_step: 1340, loss: 0.102937, Train_acc: 0.968750 Epoch:1, train_step: 1341, loss: 0.121555, Train_acc: 0.953125 Epoch:1, train_step: 1342, loss: 0.033212, Train_acc: 0.984375 Epoch:1, train_step: 1343, loss: 0.051395, Train_acc: 0.984375 Epoch:1, train_step: 1344, loss: 0.097272, Train_acc: 0.984375 Epoch:1, train_step: 1345, loss: 0.083733, Train_acc: 0.968750 Epoch:1, train_step: 1346, loss: 0.031818, Train_acc: 0.984375 Epoch:1, train_step: 1347, loss: 0.084821, Train_acc: 0.968750 Epoch:1, train_step: 1348, loss: 0.038751, Train_acc: 0.984375 Epoch:1, train_step: 1349, loss: 0.026383, Train_acc: 0.984375 Epoch:1, train_step: 1350, loss: 0.132102, Train_acc: 0.968750 Epoch:1, train_step: 1351, loss: 0.059786, Train_acc: 0.953125 Epoch:1, train_step: 1352, loss: 0.113752, Train_acc: 0.968750 Epoch:1, train_step: 1353, loss: 0.208014, Train_acc: 0.953125 Epoch:1, train_step: 1354, loss: 0.194860, Train_acc: 0.968750 Epoch:1, train_step: 1355, loss: 0.190912, Train_acc: 0.937500 Epoch:1, train_step: 1356, loss: 0.032990, Train_acc: 0.984375 Epoch:1, train_step: 1357, loss: 0.158751, Train_acc: 0.937500 Epoch:1, train_step: 1358, loss: 0.137488, Train_acc: 0.968750 Epoch:1, train_step: 1359, loss: 0.007689, Train_acc: 1.000000 Epoch:1, train_step: 1360, loss: 0.015473, Train_acc: 1.000000 Epoch:1, train_step: 1361, loss: 0.026450, Train_acc: 0.984375 Epoch:1, train_step: 1362, loss: 0.110531, Train_acc: 0.937500 Epoch:1, train_step: 1363, loss: 0.112438, Train_acc: 0.953125 Epoch:1, train_step: 1364, loss: 0.014363, Train_acc: 1.000000 Epoch:1, train_step: 1365, loss: 0.010978, Train_acc: 1.000000 Epoch:1, train_step: 1366, loss: 0.007908, Train_acc: 1.000000 Epoch:1, train_step: 1367, loss: 0.074287, Train_acc: 0.968750 Epoch:1, train_step: 1368, loss: 0.045111, Train_acc: 0.984375 Epoch:1, train_step: 1369, loss: 0.082554, Train_acc: 0.953125 Epoch:1, train_step: 1370, loss: 0.026954, Train_acc: 0.984375 Epoch:1, train_step: 1371, loss: 0.013061, Train_acc: 1.000000 Epoch:1, train_step: 1372, loss: 0.028123, Train_acc: 1.000000 Epoch:1, train_step: 1373, loss: 0.089041, Train_acc: 0.984375 Epoch:1, 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Epoch:1, train_step: 1390, loss: 0.021966, Train_acc: 1.000000 Epoch:1, train_step: 1391, loss: 0.074643, Train_acc: 0.968750 Epoch:1, train_step: 1392, loss: 0.067398, Train_acc: 0.984375 Epoch:1, train_step: 1393, loss: 0.088631, Train_acc: 0.953125 Epoch:1, train_step: 1394, loss: 0.063467, Train_acc: 0.968750 Epoch:1, train_step: 1395, loss: 0.037316, Train_acc: 0.984375 Epoch:1, train_step: 1396, loss: 0.018583, Train_acc: 1.000000 Epoch:1, train_step: 1397, loss: 0.005288, Train_acc: 1.000000 Epoch:1, train_step: 1398, loss: 0.019266, Train_acc: 1.000000 Epoch:1, train_step: 1399, loss: 0.007506, Train_acc: 1.000000 Epoch:1, train_step: 1400, loss: 0.060789, Train_acc: 0.984375 Epoch:1, train_step: 1401, loss: 0.008504, Train_acc: 1.000000 Epoch:1, train_step: 1402, loss: 0.104020, Train_acc: 0.968750 Epoch:1, train_step: 1403, loss: 0.041809, Train_acc: 0.984375 Epoch:1, train_step: 1404, loss: 0.048953, Train_acc: 1.000000 Epoch:1, train_step: 1405, loss: 0.009082, Train_acc: 1.000000 Epoch:1, train_step: 1406, loss: 0.018790, Train_acc: 1.000000 Epoch:1, train_step: 1407, loss: 0.022841, Train_acc: 1.000000 Epoch:1, train_step: 1408, loss: 0.109190, Train_acc: 0.968750 Epoch:1, train_step: 1409, loss: 0.027980, Train_acc: 1.000000 Epoch:1, train_step: 1410, loss: 0.017106, Train_acc: 1.000000 Epoch:1, train_step: 1411, loss: 0.034601, Train_acc: 0.968750 Epoch:1, train_step: 1412, loss: 0.015186, Train_acc: 0.984375 Epoch:1, train_step: 1413, loss: 0.012349, Train_acc: 1.000000 Epoch:1, train_step: 1414, loss: 0.086922, Train_acc: 0.968750 Epoch:1, train_step: 1415, loss: 0.012714, Train_acc: 1.000000 Epoch:1, train_step: 1416, loss: 0.098518, Train_acc: 0.968750 Epoch:1, train_step: 1417, loss: 0.014474, Train_acc: 1.000000 Epoch:1, train_step: 1418, loss: 0.009557, Train_acc: 1.000000 Epoch:1, train_step: 1419, loss: 0.122002, Train_acc: 0.968750 Epoch:1, train_step: 1420, loss: 0.021080, Train_acc: 1.000000 Epoch:1, train_step: 1421, loss: 0.066190, Train_acc: 0.968750 Epoch:1, train_step: 1422, loss: 0.007631, Train_acc: 1.000000 Epoch:1, train_step: 1423, loss: 0.032387, Train_acc: 0.984375 Epoch:1, train_step: 1424, loss: 0.007320, Train_acc: 1.000000 Epoch:1, train_step: 1425, loss: 0.082295, Train_acc: 0.953125 Epoch:1, train_step: 1426, loss: 0.062058, Train_acc: 0.984375 Epoch:1, train_step: 1427, loss: 0.027360, Train_acc: 1.000000 Epoch:1, train_step: 1428, loss: 0.041684, Train_acc: 0.984375 Epoch:1, train_step: 1429, loss: 0.029393, Train_acc: 0.984375 Epoch:1, train_step: 1430, loss: 0.055089, Train_acc: 0.968750 Epoch:1, train_step: 1431, loss: 0.102269, Train_acc: 0.968750 Epoch:1, train_step: 1432, loss: 0.184757, Train_acc: 0.953125 Epoch:1, train_step: 1433, loss: 0.123827, Train_acc: 0.968750 Epoch:1, train_step: 1434, loss: 0.061044, Train_acc: 0.984375 Epoch:1, train_step: 1435, loss: 0.103041, Train_acc: 0.968750 Epoch:1, train_step: 1436, loss: 0.006997, Train_acc: 1.000000 Epoch:1, train_step: 1437, loss: 0.079465, Train_acc: 0.968750 Epoch:1, train_step: 1438, loss: 0.039856, Train_acc: 0.984375 Epoch:1, train_step: 1439, loss: 0.105680, Train_acc: 0.984375 Epoch:1, train_step: 1440, loss: 0.016825, Train_acc: 1.000000 Epoch:1, train_step: 1441, loss: 0.016847, Train_acc: 1.000000 Epoch:1, train_step: 1442, loss: 0.012764, Train_acc: 1.000000 Epoch:1, train_step: 1443, loss: 0.262106, Train_acc: 0.953125 Epoch:1, train_step: 1444, loss: 0.108218, Train_acc: 0.953125 Epoch:1, train_step: 1445, loss: 0.099345, Train_acc: 0.953125 Epoch:1, train_step: 1446, loss: 0.045101, Train_acc: 0.968750 Epoch:1, train_step: 1447, loss: 0.006870, Train_acc: 1.000000 Epoch:1, train_step: 1448, loss: 0.055878, Train_acc: 0.968750 Epoch:1, train_step: 1449, loss: 0.123978, Train_acc: 0.968750 Epoch:1, train_step: 1450, loss: 0.028609, Train_acc: 0.984375 Epoch:1, train_step: 1451, loss: 0.054559, Train_acc: 0.984375 Epoch:1, train_step: 1452, loss: 0.015810, Train_acc: 1.000000 Epoch:1, train_step: 1453, loss: 0.011266, Train_acc: 1.000000 Epoch:1, train_step: 1454, loss: 0.030245, Train_acc: 0.984375 Epoch:1, train_step: 1455, loss: 0.009329, Train_acc: 1.000000 Epoch:1, train_step: 1456, loss: 0.027410, Train_acc: 0.984375 Epoch:1, train_step: 1457, loss: 0.101202, Train_acc: 0.953125 Epoch:1, train_step: 1458, loss: 0.066538, Train_acc: 0.953125 Epoch:1, train_step: 1459, loss: 0.109371, Train_acc: 0.968750 Epoch:1, train_step: 1460, loss: 0.067086, Train_acc: 0.968750 Epoch:1, train_step: 1461, loss: 0.026560, Train_acc: 0.984375 Epoch:1, train_step: 1462, loss: 0.053075, Train_acc: 0.984375 Epoch:1, train_step: 1463, loss: 0.022982, Train_acc: 0.984375 Epoch:1, train_step: 1464, loss: 0.017124, Train_acc: 1.000000 Epoch:1, train_step: 1465, loss: 0.104214, Train_acc: 0.984375 Epoch:1, train_step: 1466, loss: 0.009618, Train_acc: 1.000000 Epoch:1, train_step: 1467, loss: 0.005066, Train_acc: 1.000000 Epoch:1, train_step: 1468, loss: 0.009459, Train_acc: 1.000000 Epoch:1, train_step: 1469, loss: 0.012566, Train_acc: 1.000000 Epoch:1, train_step: 1470, loss: 0.052860, Train_acc: 0.984375 Epoch:1, train_step: 1471, loss: 0.048743, Train_acc: 0.984375 Epoch:1, train_step: 1472, loss: 0.018700, Train_acc: 1.000000 Epoch:1, train_step: 1473, loss: 0.001183, Train_acc: 1.000000 Epoch:1, train_step: 1474, loss: 0.037193, Train_acc: 0.984375 Epoch:1, train_step: 1475, loss: 0.176311, Train_acc: 0.984375 Epoch:1, train_step: 1476, loss: 0.023096, Train_acc: 1.000000 Epoch:1, train_step: 1477, loss: 0.024932, Train_acc: 0.984375 Epoch:1, train_step: 1478, loss: 0.011100, Train_acc: 1.000000 Epoch:1, train_step: 1479, loss: 0.167195, Train_acc: 0.921875 Epoch:1, train_step: 1480, loss: 0.119657, Train_acc: 0.953125 Epoch:1, train_step: 1481, loss: 0.066249, Train_acc: 0.984375 Epoch:1, train_step: 1482, loss: 0.195518, Train_acc: 0.921875 Epoch:1, train_step: 1483, loss: 0.116116, Train_acc: 0.984375 Epoch:1, train_step: 1484, loss: 0.022487, Train_acc: 0.984375 Epoch:1, train_step: 1485, loss: 0.118977, Train_acc: 0.953125 Epoch:1, train_step: 1486, loss: 0.006192, Train_acc: 1.000000 Epoch:1, train_step: 1487, loss: 0.147188, Train_acc: 0.968750 Epoch:1, train_step: 1488, loss: 0.098049, Train_acc: 0.984375 Epoch:1, train_step: 1489, loss: 0.047811, Train_acc: 0.968750 Epoch:1, train_step: 1490, loss: 0.032909, Train_acc: 0.984375 Epoch:1, train_step: 1491, loss: 0.092136, Train_acc: 0.953125 Epoch:1, train_step: 1492, loss: 0.199485, Train_acc: 0.968750 Epoch:1, train_step: 1493, loss: 0.022157, Train_acc: 0.984375 Epoch:1, train_step: 1494, loss: 0.113017, Train_acc: 0.984375 Epoch:1, train_step: 1495, loss: 0.035275, Train_acc: 0.984375 Epoch:1, train_step: 1496, loss: 0.041111, Train_acc: 0.984375 Epoch:1, train_step: 1497, loss: 0.005712, Train_acc: 1.000000 Epoch:1, train_step: 1498, loss: 0.072124, Train_acc: 0.984375 Epoch:1, train_step: 1499, loss: 0.036193, Train_acc: 0.984375 Epoch:1, train_step: 1500, loss: 0.045079, Train_acc: 0.968750 Epoch:1, train_step: 1501, loss: 0.010652, Train_acc: 1.000000 Epoch:1, train_step: 1502, loss: 0.107610, Train_acc: 0.968750 Epoch:1, train_step: 1503, loss: 0.104392, Train_acc: 0.968750 Epoch:1, train_step: 1504, loss: 0.040792, Train_acc: 0.984375 Epoch:1, train_step: 1505, loss: 0.004938, Train_acc: 1.000000 Epoch:1, train_step: 1506, loss: 0.033377, Train_acc: 0.984375 Epoch:1, train_step: 1507, loss: 0.102245, Train_acc: 0.984375 Epoch:1, train_step: 1508, loss: 0.039939, Train_acc: 0.984375 Epoch:1, train_step: 1509, loss: 0.004771, Train_acc: 1.000000 Epoch:1, train_step: 1510, loss: 0.042302, Train_acc: 0.984375 Epoch:1, train_step: 1511, loss: 0.106108, Train_acc: 0.968750 Epoch:1, train_step: 1512, loss: 0.106924, Train_acc: 0.968750 Epoch:1, train_step: 1513, loss: 0.018975, Train_acc: 1.000000 Epoch:1, train_step: 1514, loss: 0.006965, Train_acc: 1.000000 Epoch:1, train_step: 1515, loss: 0.046238, Train_acc: 0.984375 Epoch:1, train_step: 1516, loss: 0.132284, Train_acc: 0.984375 Epoch:1, train_step: 1517, loss: 0.083051, Train_acc: 0.968750 Epoch:1, train_step: 1518, loss: 0.040068, Train_acc: 1.000000 Epoch:1, train_step: 1519, loss: 0.016003, Train_acc: 1.000000 Epoch:1, train_step: 1520, loss: 0.008888, Train_acc: 1.000000 Epoch:1, train_step: 1521, loss: 0.037262, Train_acc: 0.984375 Epoch:1, train_step: 1522, loss: 0.102939, Train_acc: 0.968750 Epoch:1, train_step: 1523, loss: 0.031399, Train_acc: 0.984375 Epoch:1, train_step: 1524, loss: 0.023379, Train_acc: 1.000000 Epoch:1, train_step: 1525, loss: 0.006697, Train_acc: 1.000000 Epoch:1, train_step: 1526, loss: 0.024089, Train_acc: 1.000000 Epoch:1, train_step: 1527, loss: 0.110019, Train_acc: 0.953125 Epoch:1, train_step: 1528, loss: 0.038117, Train_acc: 0.984375 Epoch:1, train_step: 1529, loss: 0.182781, Train_acc: 0.968750 Epoch:1, train_step: 1530, loss: 0.020586, Train_acc: 1.000000 Epoch:1, train_step: 1531, loss: 0.011696, Train_acc: 1.000000 Epoch:1, train_step: 1532, loss: 0.018343, Train_acc: 1.000000 Epoch:1, train_step: 1533, loss: 0.014916, Train_acc: 1.000000 Epoch:1, train_step: 1534, loss: 0.007000, Train_acc: 1.000000 Epoch:1, train_step: 1535, loss: 0.021754, Train_acc: 1.000000 Epoch:1, train_step: 1536, loss: 0.022012, Train_acc: 1.000000 Epoch:1, train_step: 1537, loss: 0.037628, Train_acc: 0.984375 Epoch:1, train_step: 1538, loss: 0.076586, Train_acc: 0.984375 Epoch:1, train_step: 1539, loss: 0.062558, Train_acc: 0.984375 Epoch:1, train_step: 1540, loss: 0.009810, Train_acc: 1.000000 Epoch:1, train_step: 1541, loss: 0.070632, Train_acc: 0.968750 Epoch:1, train_step: 1542, loss: 0.108446, Train_acc: 0.984375 Epoch:1, train_step: 1543, loss: 0.081091, Train_acc: 0.984375 Epoch:1, train_step: 1544, loss: 0.008270, Train_acc: 1.000000 Epoch:1, train_step: 1545, loss: 0.058256, Train_acc: 0.984375 Epoch:1, train_step: 1546, loss: 0.012058, Train_acc: 1.000000 Epoch:1, train_step: 1547, loss: 0.056900, Train_acc: 0.984375 Epoch:1, train_step: 1548, loss: 0.001679, Train_acc: 1.000000 Epoch:1, train_step: 1549, loss: 0.002834, Train_acc: 1.000000 Epoch:1, train_step: 1550, loss: 0.128192, Train_acc: 0.984375 Epoch:1, train_step: 1551, loss: 0.088445, Train_acc: 0.953125 Epoch:1, train_step: 1552, loss: 0.109626, Train_acc: 0.953125 Epoch:1, train_step: 1553, loss: 0.177591, Train_acc: 0.937500 Epoch:1, train_step: 1554, loss: 0.071008, Train_acc: 0.953125 Epoch:1, train_step: 1555, loss: 0.013359, Train_acc: 1.000000 Epoch:1, train_step: 1556, loss: 0.030344, Train_acc: 0.984375 Epoch:1, train_step: 1557, loss: 0.082561, Train_acc: 0.968750 Epoch:1, train_step: 1558, loss: 0.067915, Train_acc: 0.968750 Epoch:1, train_step: 1559, loss: 0.065795, Train_acc: 0.968750 Epoch:1, train_step: 1560, loss: 0.045558, Train_acc: 0.984375 Epoch:1, train_step: 1561, loss: 0.020929, Train_acc: 1.000000 Epoch:1, train_step: 1562, loss: 0.083318, Train_acc: 0.968750 Epoch:1, train_step: 1563, loss: 0.044118, Train_acc: 0.968750 Epoch:1, train_step: 1564, loss: 0.028541, Train_acc: 1.000000 Epoch:1, train_step: 1565, loss: 0.167750, Train_acc: 0.984375 Epoch:1, train_step: 1566, loss: 0.015090, Train_acc: 1.000000 Epoch:1, train_step: 1567, loss: 0.075590, Train_acc: 0.984375 Epoch:1, train_step: 1568, loss: 0.081535, Train_acc: 0.984375 Epoch:1, train_step: 1569, loss: 0.075826, Train_acc: 0.984375 Epoch:1, train_step: 1570, loss: 0.007978, Train_acc: 1.000000 Epoch:1, train_step: 1571, loss: 0.070151, Train_acc: 0.968750 Epoch:1, train_step: 1572, loss: 0.073094, Train_acc: 0.984375 Epoch:1, train_step: 1573, loss: 0.067692, Train_acc: 0.984375 Epoch:1, train_step: 1574, loss: 0.107996, Train_acc: 0.968750 Epoch:1, train_step: 1575, loss: 0.011892, Train_acc: 1.000000 Epoch:1, train_step: 1576, loss: 0.048413, Train_acc: 0.984375 Epoch:1, train_step: 1577, loss: 0.076095, Train_acc: 0.968750 Epoch:1, train_step: 1578, loss: 0.148439, Train_acc: 0.953125 Epoch:1, train_step: 1579, loss: 0.022421, Train_acc: 0.984375 Epoch:1, train_step: 1580, loss: 0.005690, Train_acc: 1.000000 Epoch:1, train_step: 1581, loss: 0.032629, Train_acc: 0.984375 Epoch:1, train_step: 1582, loss: 0.091024, Train_acc: 0.953125 Epoch:1, train_step: 1583, loss: 0.129509, Train_acc: 0.953125 Epoch:1, train_step: 1584, loss: 0.173019, Train_acc: 0.968750 Epoch:1, train_step: 1585, loss: 0.054148, Train_acc: 0.984375 Epoch:1, train_step: 1586, loss: 0.017405, Train_acc: 1.000000 Epoch:1, train_step: 1587, loss: 0.029871, Train_acc: 0.984375 Epoch:1, train_step: 1588, loss: 0.082979, Train_acc: 0.984375 Epoch:1, train_step: 1589, loss: 0.010512, Train_acc: 1.000000 Epoch:1, train_step: 1590, loss: 0.052090, Train_acc: 0.984375 Epoch:1, train_step: 1591, loss: 0.062954, Train_acc: 0.984375 Epoch:1, train_step: 1592, loss: 0.083635, Train_acc: 0.968750 Epoch:1, train_step: 1593, loss: 0.004433, Train_acc: 1.000000 Epoch:1, train_step: 1594, loss: 0.102816, Train_acc: 0.953125 Epoch:1, train_step: 1595, loss: 0.016091, Train_acc: 1.000000 Epoch:1, train_step: 1596, loss: 0.030606, Train_acc: 0.984375 Epoch:1, train_step: 1597, loss: 0.017198, Train_acc: 1.000000 Epoch:1, train_step: 1598, loss: 0.006278, Train_acc: 1.000000 Epoch:1, train_step: 1599, loss: 0.066523, Train_acc: 0.984375 Epoch:1, train_step: 1600, loss: 0.032470, Train_acc: 1.000000 Epoch:1, train_step: 1601, loss: 0.077193, Train_acc: 0.984375 Epoch:1, train_step: 1602, loss: 0.013265, Train_acc: 1.000000 Epoch:1, train_step: 1603, loss: 0.129515, Train_acc: 0.984375 Epoch:1, train_step: 1604, loss: 0.079876, Train_acc: 0.984375 Epoch:1, train_step: 1605, loss: 0.015331, Train_acc: 1.000000 Epoch:1, train_step: 1606, loss: 0.011707, Train_acc: 1.000000 Epoch:1, train_step: 1607, loss: 0.073284, Train_acc: 0.968750 Epoch:1, train_step: 1608, loss: 0.040354, Train_acc: 0.984375 Epoch:1, train_step: 1609, loss: 0.064418, Train_acc: 0.953125 Epoch:1, train_step: 1610, loss: 0.094358, Train_acc: 0.968750 Epoch:1, train_step: 1611, loss: 0.185966, Train_acc: 0.953125 Epoch:1, train_step: 1612, loss: 0.038960, Train_acc: 0.984375 Epoch:1, train_step: 1613, loss: 0.013407, Train_acc: 1.000000 Epoch:1, train_step: 1614, loss: 0.004283, Train_acc: 1.000000 Epoch:1, train_step: 1615, loss: 0.012572, Train_acc: 1.000000 Epoch:1, train_step: 1616, loss: 0.159360, Train_acc: 0.984375 Epoch:1, train_step: 1617, loss: 0.031045, Train_acc: 0.984375 Epoch:1, train_step: 1618, loss: 0.085698, Train_acc: 0.968750 Epoch:1, train_step: 1619, loss: 0.020301, Train_acc: 0.984375 Epoch:1, train_step: 1620, loss: 0.161103, Train_acc: 0.968750 Epoch:1, train_step: 1621, loss: 0.002720, Train_acc: 1.000000 Epoch:1, train_step: 1622, loss: 0.029937, Train_acc: 0.984375 Epoch:1, train_step: 1623, loss: 0.015325, Train_acc: 1.000000 Epoch:1, train_step: 1624, loss: 0.013862, Train_acc: 1.000000 Epoch:1, train_step: 1625, loss: 0.041613, Train_acc: 0.984375 Epoch:1, train_step: 1626, loss: 0.050298, Train_acc: 0.984375 Epoch:1, train_step: 1627, loss: 0.025255, Train_acc: 0.984375 Epoch:1, train_step: 1628, loss: 0.004819, Train_acc: 1.000000 Epoch:1, train_step: 1629, loss: 0.065883, Train_acc: 0.984375 Epoch:1, train_step: 1630, loss: 0.018681, Train_acc: 0.984375 Epoch:1, train_step: 1631, loss: 0.059535, Train_acc: 0.984375 Epoch:1, train_step: 1632, loss: 0.057903, Train_acc: 0.968750 Epoch:1, train_step: 1633, loss: 0.011747, Train_acc: 1.000000 Epoch:1, train_step: 1634, loss: 0.004930, Train_acc: 1.000000 Epoch:1, train_step: 1635, loss: 0.008048, Train_acc: 1.000000 Epoch:1, train_step: 1636, loss: 0.010005, Train_acc: 1.000000 Epoch:1, train_step: 1637, loss: 0.017185, Train_acc: 1.000000 Epoch:1, train_step: 1638, loss: 0.130003, Train_acc: 0.968750 Epoch:1, train_step: 1639, loss: 0.016370, Train_acc: 1.000000 Epoch:1, train_step: 1640, loss: 0.008722, Train_acc: 1.000000 Epoch:1, train_step: 1641, loss: 0.017198, Train_acc: 1.000000 Epoch:1, train_step: 1642, loss: 0.012065, Train_acc: 1.000000 Epoch:1, train_step: 1643, loss: 0.079113, Train_acc: 0.984375 Epoch:1, train_step: 1644, loss: 0.004725, Train_acc: 1.000000 Epoch:1, train_step: 1645, loss: 0.013309, Train_acc: 1.000000 Epoch:1, train_step: 1646, loss: 0.070735, Train_acc: 0.984375 Epoch:1, train_step: 1647, loss: 0.022233, Train_acc: 1.000000 Epoch:1, train_step: 1648, loss: 0.014732, Train_acc: 1.000000 Epoch:1, train_step: 1649, loss: 0.074380, Train_acc: 0.984375 Epoch:1, train_step: 1650, loss: 0.089247, Train_acc: 0.968750 Epoch:1, train_step: 1651, loss: 0.023913, Train_acc: 1.000000 Epoch:1, train_step: 1652, loss: 0.018053, Train_acc: 1.000000 Epoch:1, train_step: 1653, loss: 0.058496, Train_acc: 0.968750 Epoch:1, train_step: 1654, loss: 0.107786, Train_acc: 0.984375 Epoch:1, train_step: 1655, loss: 0.044408, Train_acc: 0.968750 Epoch:1, train_step: 1656, loss: 0.141514, Train_acc: 0.953125 Epoch:1, train_step: 1657, loss: 0.080544, Train_acc: 0.968750 Epoch:1, train_step: 1658, loss: 0.086222, Train_acc: 0.953125 Epoch:1, train_step: 1659, loss: 0.014233, Train_acc: 1.000000 Epoch:1, train_step: 1660, loss: 0.076184, Train_acc: 0.968750 Epoch:1, train_step: 1661, loss: 0.060892, Train_acc: 0.984375 Epoch:1, train_step: 1662, loss: 0.032306, Train_acc: 0.984375 Epoch:1, train_step: 1663, loss: 0.040733, Train_acc: 1.000000 Epoch:1, train_step: 1664, loss: 0.009471, Train_acc: 1.000000 Epoch:1, train_step: 1665, loss: 0.005519, Train_acc: 1.000000 Epoch:1, train_step: 1666, loss: 0.023039, Train_acc: 0.984375 Epoch:1, train_step: 1667, loss: 0.089492, Train_acc: 0.984375 Epoch:1, train_step: 1668, loss: 0.069719, Train_acc: 0.984375 Epoch:1, train_step: 1669, loss: 0.034170, Train_acc: 0.984375 Epoch:1, train_step: 1670, loss: 0.092907, Train_acc: 0.984375 Epoch:1, train_step: 1671, loss: 0.011993, Train_acc: 1.000000 Epoch:1, train_step: 1672, loss: 0.082502, Train_acc: 0.984375 Epoch:1, train_step: 1673, loss: 0.029105, Train_acc: 0.984375 Epoch:1, train_step: 1674, loss: 0.092391, Train_acc: 0.953125 Epoch:1, train_step: 1675, loss: 0.039839, Train_acc: 0.984375 Epoch:1, train_step: 1676, loss: 0.119613, Train_acc: 0.953125 Epoch:1, train_step: 1677, loss: 0.029298, Train_acc: 0.984375 Epoch:1, train_step: 1678, loss: 0.049658, Train_acc: 0.984375 Epoch:1, train_step: 1679, loss: 0.097120, Train_acc: 0.968750 Epoch:1, train_step: 1680, loss: 0.032238, Train_acc: 0.984375 Epoch:1, train_step: 1681, loss: 0.173200, Train_acc: 0.953125 Epoch:1, train_step: 1682, loss: 0.020796, Train_acc: 1.000000 Epoch:1, train_step: 1683, loss: 0.159190, Train_acc: 0.953125 Epoch:1, train_step: 1684, loss: 0.080437, Train_acc: 0.968750 Epoch:1, train_step: 1685, loss: 0.022113, Train_acc: 1.000000 Epoch:1, train_step: 1686, loss: 0.063797, Train_acc: 0.968750 Epoch:1, train_step: 1687, loss: 0.022494, Train_acc: 1.000000 Epoch:1, train_step: 1688, loss: 0.020349, Train_acc: 1.000000 Epoch:1, train_step: 1689, loss: 0.085822, Train_acc: 0.953125 Epoch:1, train_step: 1690, loss: 0.005409, Train_acc: 1.000000 Epoch:1, train_step: 1691, loss: 0.028855, Train_acc: 0.984375 Epoch:1, train_step: 1692, loss: 0.028847, Train_acc: 0.984375 Epoch:1, train_step: 1693, loss: 0.081878, Train_acc: 0.984375 Epoch:1, train_step: 1694, loss: 0.007568, Train_acc: 1.000000 Epoch:1, train_step: 1695, loss: 0.019306, Train_acc: 1.000000 Epoch:1, train_step: 1696, loss: 0.035546, Train_acc: 0.984375 Epoch:1, train_step: 1697, loss: 0.017789, Train_acc: 1.000000 Epoch:1, train_step: 1698, loss: 0.029162, Train_acc: 1.000000 Epoch:1, train_step: 1699, loss: 0.008407, Train_acc: 1.000000 Epoch:1, train_step: 1700, loss: 0.026606, Train_acc: 0.984375 Epoch:1, train_step: 1701, loss: 0.041978, Train_acc: 0.984375 Epoch:1, train_step: 1702, loss: 0.044890, Train_acc: 1.000000 Epoch:1, train_step: 1703, loss: 0.244183, Train_acc: 0.921875 Epoch:1, train_step: 1704, loss: 0.158519, Train_acc: 0.968750 Epoch:1, train_step: 1705, loss: 0.010329, Train_acc: 1.000000 Epoch:1, train_step: 1706, loss: 0.167046, Train_acc: 0.968750 Epoch:1, train_step: 1707, loss: 0.027354, Train_acc: 0.984375 Epoch:1, train_step: 1708, loss: 0.005591, Train_acc: 1.000000 Epoch:1, train_step: 1709, loss: 0.037072, Train_acc: 0.984375 Epoch:1, train_step: 1710, loss: 0.147422, Train_acc: 0.953125 Epoch:1, train_step: 1711, loss: 0.109685, Train_acc: 0.968750 Epoch:1, train_step: 1712, loss: 0.054842, Train_acc: 0.968750 Epoch:1, train_step: 1713, loss: 0.023478, Train_acc: 0.984375 Epoch:1, train_step: 1714, loss: 0.021057, Train_acc: 1.000000 Epoch:1, train_step: 1715, loss: 0.055469, Train_acc: 0.984375 Epoch:1, train_step: 1716, loss: 0.025409, Train_acc: 0.984375 Epoch:1, train_step: 1717, loss: 0.069352, Train_acc: 0.953125 Epoch:1, train_step: 1718, loss: 0.015434, Train_acc: 1.000000 Epoch:1, train_step: 1719, loss: 0.009202, Train_acc: 1.000000 Epoch:1, train_step: 1720, loss: 0.013941, Train_acc: 1.000000 Epoch:1, train_step: 1721, loss: 0.007692, Train_acc: 1.000000 Epoch:1, train_step: 1722, loss: 0.036477, Train_acc: 0.984375 Epoch:1, train_step: 1723, loss: 0.010282, Train_acc: 1.000000 Epoch:1, train_step: 1724, loss: 0.053968, Train_acc: 0.984375 Epoch:1, train_step: 1725, loss: 0.048720, Train_acc: 0.984375 Epoch:1, train_step: 1726, loss: 0.016889, Train_acc: 1.000000 Epoch:1, train_step: 1727, loss: 0.072172, Train_acc: 0.984375 Epoch:1, train_step: 1728, loss: 0.048062, Train_acc: 0.968750 Epoch:1, train_step: 1729, loss: 0.001926, Train_acc: 1.000000 Epoch:1, train_step: 1730, loss: 0.025171, Train_acc: 1.000000 Epoch:1, train_step: 1731, loss: 0.007335, Train_acc: 1.000000 Epoch:1, train_step: 1732, loss: 0.009793, Train_acc: 1.000000 Epoch:1, train_step: 1733, loss: 0.055896, Train_acc: 0.968750 Epoch:1, train_step: 1734, loss: 0.089053, Train_acc: 0.968750 Epoch:1, train_step: 1735, loss: 0.004545, Train_acc: 1.000000 Epoch:1, train_step: 1736, loss: 0.002600, Train_acc: 1.000000 Epoch:1, train_step: 1737, loss: 0.015825, Train_acc: 1.000000 Epoch:1, train_step: 1738, loss: 0.092358, Train_acc: 0.968750 Epoch:1, train_step: 1739, loss: 0.037471, Train_acc: 0.984375 Epoch:1, train_step: 1740, loss: 0.049103, Train_acc: 0.984375 Epoch:1, train_step: 1741, loss: 0.041438, Train_acc: 0.968750 Epoch:1, train_step: 1742, loss: 0.029007, Train_acc: 0.984375 Epoch:1, train_step: 1743, loss: 0.011783, Train_acc: 1.000000 Epoch:1, train_step: 1744, loss: 0.011957, Train_acc: 1.000000 Epoch:1, train_step: 1745, loss: 0.060932, Train_acc: 0.984375 Epoch:1, train_step: 1746, loss: 0.062116, Train_acc: 0.984375 Epoch:1, train_step: 1747, loss: 0.003493, Train_acc: 1.000000 Epoch:1, train_step: 1748, loss: 0.004304, Train_acc: 1.000000 Epoch:1, train_step: 1749, loss: 0.124298, Train_acc: 0.984375 Epoch:1, train_step: 1750, loss: 0.056901, Train_acc: 0.984375 Epoch:1, train_step: 1751, loss: 0.008309, Train_acc: 1.000000 Epoch:1, train_step: 1752, loss: 0.057649, Train_acc: 0.968750 Epoch:1, train_step: 1753, loss: 0.077888, Train_acc: 0.968750 Epoch:1, train_step: 1754, loss: 0.011772, Train_acc: 1.000000 Epoch:1, train_step: 1755, loss: 0.039106, Train_acc: 0.984375 Epoch:1, train_step: 1756, loss: 0.013586, Train_acc: 1.000000 Epoch:1, train_step: 1757, loss: 0.036578, Train_acc: 0.984375 Epoch:1, train_step: 1758, loss: 0.015817, Train_acc: 1.000000 Epoch:1, train_step: 1759, loss: 0.008866, Train_acc: 1.000000 Epoch:1, train_step: 1760, loss: 0.004995, Train_acc: 1.000000 Epoch:1, train_step: 1761, loss: 0.012170, Train_acc: 1.000000 Epoch:1, train_step: 1762, loss: 0.024324, Train_acc: 1.000000 Epoch:1, train_step: 1763, loss: 0.123443, Train_acc: 0.968750 Epoch:1, train_step: 1764, loss: 0.056428, Train_acc: 0.984375 Epoch:1, train_step: 1765, loss: 0.346876, Train_acc: 0.953125 Epoch:1, train_step: 1766, loss: 0.005921, Train_acc: 1.000000 Epoch:1, train_step: 1767, loss: 0.005686, Train_acc: 1.000000 Epoch:1, train_step: 1768, loss: 0.030143, Train_acc: 1.000000 Epoch:1, train_step: 1769, loss: 0.058174, Train_acc: 0.984375 Epoch:1, train_step: 1770, loss: 0.012629, Train_acc: 1.000000 Epoch:1, train_step: 1771, loss: 0.008110, Train_acc: 1.000000 Epoch:1, train_step: 1772, loss: 0.071616, Train_acc: 0.984375 Epoch:1, train_step: 1773, loss: 0.022374, Train_acc: 1.000000 Epoch:1, train_step: 1774, loss: 0.026213, Train_acc: 1.000000 Epoch:1, train_step: 1775, loss: 0.007081, Train_acc: 1.000000 Epoch:1, train_step: 1776, loss: 0.112083, Train_acc: 0.953125 Epoch:1, train_step: 1777, loss: 0.014607, Train_acc: 1.000000 Epoch:1, train_step: 1778, loss: 0.036364, Train_acc: 0.984375 Epoch:1, train_step: 1779, loss: 0.032702, Train_acc: 0.984375 Epoch:1, train_step: 1780, loss: 0.011502, Train_acc: 1.000000 Epoch:1, train_step: 1781, loss: 0.050995, Train_acc: 0.984375 Epoch:1, train_step: 1782, loss: 0.068551, Train_acc: 0.968750 Epoch:1, train_step: 1783, loss: 0.022688, Train_acc: 1.000000 Epoch:1, train_step: 1784, loss: 0.030481, Train_acc: 0.984375 Epoch:1, train_step: 1785, loss: 0.032350, Train_acc: 0.984375 Epoch:1, train_step: 1786, loss: 0.069258, Train_acc: 0.984375 Epoch:1, train_step: 1787, loss: 0.013405, Train_acc: 1.000000 Epoch:1, train_step: 1788, loss: 0.012626, Train_acc: 1.000000 Epoch:1, train_step: 1789, loss: 0.011884, Train_acc: 1.000000 Epoch:1, train_step: 1790, loss: 0.020724, Train_acc: 1.000000 Epoch:1, train_step: 1791, loss: 0.026241, Train_acc: 0.984375 Epoch:1, train_step: 1792, loss: 0.009173, Train_acc: 1.000000 Epoch:1, train_step: 1793, loss: 0.021020, Train_acc: 1.000000 Epoch:1, train_step: 1794, loss: 0.044317, Train_acc: 0.984375 Epoch:1, train_step: 1795, loss: 0.093904, Train_acc: 0.984375 Epoch:1, train_step: 1796, loss: 0.012059, Train_acc: 1.000000 Epoch:1, train_step: 1797, loss: 0.007944, Train_acc: 1.000000 Epoch:1, train_step: 1798, loss: 0.015315, Train_acc: 1.000000 Epoch:1, train_step: 1799, loss: 0.009105, Train_acc: 1.000000 Epoch:1, train_step: 1800, loss: 0.007966, Train_acc: 1.000000 Epoch:1, train_step: 1801, loss: 0.038789, Train_acc: 0.968750 Epoch:1, train_step: 1802, loss: 0.069789, Train_acc: 0.984375 Epoch:1, train_step: 1803, loss: 0.074268, Train_acc: 0.984375 Epoch:1, train_step: 1804, loss: 0.052971, Train_acc: 0.968750 Epoch:1, train_step: 1805, loss: 0.021473, Train_acc: 1.000000 Epoch:1, train_step: 1806, loss: 0.187349, Train_acc: 0.906250 Epoch:1, train_step: 1807, loss: 0.009108, Train_acc: 1.000000 Epoch:1, train_step: 1808, loss: 0.056710, Train_acc: 0.984375 Epoch:1, train_step: 1809, loss: 0.013982, Train_acc: 1.000000 Epoch:1, train_step: 1810, loss: 0.008763, Train_acc: 1.000000 Epoch:1, train_step: 1811, loss: 0.018516, Train_acc: 0.984375 Epoch:1, train_step: 1812, loss: 0.007913, Train_acc: 1.000000 Epoch:1, train_step: 1813, loss: 0.035344, Train_acc: 0.984375 Epoch:1, train_step: 1814, loss: 0.025418, Train_acc: 1.000000 Epoch:1, train_step: 1815, loss: 0.089421, Train_acc: 0.984375 Epoch:1, train_step: 1816, loss: 0.072652, Train_acc: 0.968750 Epoch:1, train_step: 1817, loss: 0.021188, Train_acc: 1.000000 Epoch:1, train_step: 1818, loss: 0.029620, Train_acc: 0.984375 Epoch:1, train_step: 1819, loss: 0.075182, Train_acc: 0.968750 Epoch:1, train_step: 1820, loss: 0.112076, Train_acc: 0.968750 Epoch:1, train_step: 1821, loss: 0.001839, Train_acc: 1.000000 Epoch:1, train_step: 1822, loss: 0.032965, Train_acc: 0.984375 Epoch:1, train_step: 1823, loss: 0.020017, Train_acc: 0.984375 Epoch:1, train_step: 1824, loss: 0.012038, Train_acc: 1.000000 Epoch:1, train_step: 1825, loss: 0.125250, Train_acc: 0.968750 Epoch:1, train_step: 1826, loss: 0.031676, Train_acc: 0.984375 Epoch:1, train_step: 1827, loss: 0.017276, Train_acc: 0.984375 Epoch:1, train_step: 1828, loss: 0.015320, Train_acc: 1.000000 Epoch:1, train_step: 1829, loss: 0.021616, Train_acc: 1.000000 Epoch:1, train_step: 1830, loss: 0.001809, Train_acc: 1.000000 Epoch:1, train_step: 1831, loss: 0.003316, Train_acc: 1.000000 Epoch:1, train_step: 1832, loss: 0.057030, Train_acc: 0.984375 Epoch:1, train_step: 1833, loss: 0.027074, Train_acc: 1.000000 Epoch:1, train_step: 1834, loss: 0.005355, Train_acc: 1.000000 Epoch:1, train_step: 1835, loss: 0.029019, Train_acc: 0.984375 Epoch:1, train_step: 1836, loss: 0.042131, Train_acc: 0.984375 Epoch:1, train_step: 1837, loss: 0.005670, Train_acc: 1.000000 Epoch:1, train_step: 1838, loss: 0.071209, Train_acc: 0.968750 Epoch:1, train_step: 1839, loss: 0.030052, Train_acc: 1.000000 Epoch:1, train_step: 1840, loss: 0.209030, Train_acc: 0.937500 Epoch:1, train_step: 1841, loss: 0.108574, Train_acc: 0.937500 Epoch:1, train_step: 1842, loss: 0.007739, Train_acc: 1.000000 Epoch:1, train_step: 1843, loss: 0.050842, Train_acc: 0.968750 Epoch:1, train_step: 1844, loss: 0.007601, Train_acc: 1.000000 Epoch:1, train_step: 1845, loss: 0.121161, Train_acc: 0.953125 Epoch:1, train_step: 1846, loss: 0.007328, Train_acc: 1.000000 Epoch:1, train_step: 1847, loss: 0.011932, Train_acc: 0.984375 Epoch:1, train_step: 1848, loss: 0.001456, Train_acc: 1.000000 Epoch:1, train_step: 1849, loss: 0.017428, Train_acc: 0.984375 Epoch:1, train_step: 1850, loss: 0.027469, Train_acc: 0.984375 Epoch:1, train_step: 1851, loss: 0.070726, Train_acc: 0.968750 Epoch:1, train_step: 1852, loss: 0.004458, Train_acc: 1.000000 Epoch:1, train_step: 1853, loss: 0.003107, Train_acc: 1.000000 Epoch:1, train_step: 1854, loss: 0.015542, Train_acc: 1.000000 Epoch:1, train_step: 1855, loss: 0.000285, Train_acc: 1.000000 Epoch:1, train_step: 1856, loss: 0.061825, Train_acc: 0.984375 Epoch:1, train_step: 1857, loss: 0.044111, Train_acc: 0.984375 Epoch:1, train_step: 1858, loss: 0.001302, Train_acc: 1.000000 Epoch:1, train_step: 1859, loss: 0.000769, Train_acc: 1.000000 Epoch:1, train_step: 1860, loss: 0.000962, Train_acc: 1.000000 Epoch:1, train_step: 1861, loss: 0.000630, Train_acc: 1.000000 Epoch:1, train_step: 1862, loss: 0.000315, Train_acc: 1.000000 Epoch:1, train_step: 1863, loss: 0.000948, Train_acc: 1.000000 Epoch:1, train_step: 1864, loss: 0.010800, Train_acc: 1.000000 Epoch:1, train_step: 1865, loss: 0.041330, Train_acc: 0.984375 Epoch:1, train_step: 1866, loss: 0.002359, Train_acc: 1.000000 Epoch:1, train_step: 1867, loss: 0.005621, Train_acc: 1.000000 Epoch:1, train_step: 1868, loss: 0.000917, Train_acc: 1.000000 Epoch:1, train_step: 1869, loss: 0.018762, Train_acc: 0.984375 Epoch:1, train_step: 1870, loss: 0.109288, Train_acc: 0.953125 Epoch:1, train_step: 1871, loss: 0.288927, Train_acc: 0.937500 Epoch:1, train_step: 1872, loss: 0.017636, Train_acc: 0.984375 Epoch:1, train_step: 1873, loss: 0.001580, Train_acc: 1.000000 Epoch:1, train_step: 1874, loss: 0.194396, Train_acc: 0.984375 Epoch:1, avg_train_loss: 0.052591, avg_train_acc: 0.984125, Test_acc: 0.979768 Epoch:2, train_step: 1875, loss: 0.023960, Train_acc: 0.984375 Epoch:2, train_step: 1876, loss: 0.063411, Train_acc: 0.984375 Epoch:2, train_step: 1877, loss: 0.240169, Train_acc: 0.968750 Epoch:2, train_step: 1878, loss: 0.065802, Train_acc: 0.968750 Epoch:2, train_step: 1879, loss: 0.042118, Train_acc: 0.984375 Epoch:2, train_step: 1880, loss: 0.009022, Train_acc: 1.000000 Epoch:2, train_step: 1881, loss: 0.030457, Train_acc: 0.984375 Epoch:2, train_step: 1882, loss: 0.174054, Train_acc: 0.968750 Epoch:2, train_step: 1883, loss: 0.009489, Train_acc: 1.000000 Epoch:2, train_step: 1884, loss: 0.160137, Train_acc: 0.984375 Epoch:2, train_step: 1885, loss: 0.005727, Train_acc: 1.000000 Epoch:2, train_step: 1886, loss: 0.033890, Train_acc: 0.984375 Epoch:2, train_step: 1887, loss: 0.058954, Train_acc: 0.984375 Epoch:2, train_step: 1888, loss: 0.065088, Train_acc: 0.968750 Epoch:2, train_step: 1889, loss: 0.110371, Train_acc: 0.968750 Epoch:2, train_step: 1890, loss: 0.080671, Train_acc: 0.984375 Epoch:2, train_step: 1891, loss: 0.039509, Train_acc: 1.000000 Epoch:2, train_step: 1892, loss: 0.080851, Train_acc: 0.968750 Epoch:2, train_step: 1893, loss: 0.027604, Train_acc: 1.000000 Epoch:2, train_step: 1894, loss: 0.019986, Train_acc: 1.000000 Epoch:2, train_step: 1895, loss: 0.044996, Train_acc: 0.984375 Epoch:2, train_step: 1896, loss: 0.094933, Train_acc: 0.953125 Epoch:2, train_step: 1897, loss: 0.004534, Train_acc: 1.000000 Epoch:2, train_step: 1898, loss: 0.031015, Train_acc: 0.984375 Epoch:2, train_step: 1899, loss: 0.012059, Train_acc: 1.000000 Epoch:2, train_step: 1900, loss: 0.147273, Train_acc: 0.968750 Epoch:2, train_step: 1901, loss: 0.017002, Train_acc: 1.000000 Epoch:2, train_step: 1902, loss: 0.120555, Train_acc: 0.968750 Epoch:2, train_step: 1903, loss: 0.023446, Train_acc: 1.000000 Epoch:2, train_step: 1904, loss: 0.005364, Train_acc: 1.000000 Epoch:2, train_step: 1905, loss: 0.046077, Train_acc: 0.984375 Epoch:2, train_step: 1906, loss: 0.008177, Train_acc: 1.000000 Epoch:2, train_step: 1907, loss: 0.015399, Train_acc: 1.000000 Epoch:2, train_step: 1908, loss: 0.054910, Train_acc: 0.984375 Epoch:2, train_step: 1909, loss: 0.034569, Train_acc: 0.984375 Epoch:2, train_step: 1910, loss: 0.018546, Train_acc: 1.000000 Epoch:2, train_step: 1911, loss: 0.007902, Train_acc: 1.000000 Epoch:2, train_step: 1912, loss: 0.069716, Train_acc: 0.984375 Epoch:2, train_step: 1913, loss: 0.004114, Train_acc: 1.000000 Epoch:2, train_step: 1914, loss: 0.030129, Train_acc: 0.984375 Epoch:2, train_step: 1915, loss: 0.031083, Train_acc: 0.984375 Epoch:2, train_step: 1916, loss: 0.073787, Train_acc: 0.984375 Epoch:2, train_step: 1917, loss: 0.137437, Train_acc: 0.953125 Epoch:2, train_step: 1918, loss: 0.012591, Train_acc: 1.000000 Epoch:2, train_step: 1919, loss: 0.020201, Train_acc: 0.984375 Epoch:2, train_step: 1920, loss: 0.010786, Train_acc: 1.000000 Epoch:2, train_step: 1921, loss: 0.006952, Train_acc: 1.000000 Epoch:2, train_step: 1922, loss: 0.020520, Train_acc: 1.000000 Epoch:2, train_step: 1923, loss: 0.006916, Train_acc: 1.000000 Epoch:2, train_step: 1924, loss: 0.001710, Train_acc: 1.000000 Epoch:2, train_step: 1925, loss: 0.086597, Train_acc: 0.984375 Epoch:2, train_step: 1926, loss: 0.016185, Train_acc: 1.000000 Epoch:2, train_step: 1927, loss: 0.006305, Train_acc: 1.000000 Epoch:2, train_step: 1928, loss: 0.024834, Train_acc: 0.984375 Epoch:2, train_step: 1929, loss: 0.066062, Train_acc: 0.968750 Epoch:2, train_step: 1930, loss: 0.009396, Train_acc: 1.000000 Epoch:2, train_step: 1931, loss: 0.012777, Train_acc: 1.000000 Epoch:2, train_step: 1932, loss: 0.398243, Train_acc: 0.921875 Epoch:2, train_step: 1933, loss: 0.040733, Train_acc: 0.984375 Epoch:2, train_step: 1934, loss: 0.008559, Train_acc: 1.000000 Epoch:2, train_step: 1935, loss: 0.003255, Train_acc: 1.000000 Epoch:2, train_step: 1936, loss: 0.046137, Train_acc: 0.984375 Epoch:2, train_step: 1937, loss: 0.030870, Train_acc: 0.984375 Epoch:2, train_step: 1938, loss: 0.011372, Train_acc: 1.000000 Epoch:2, train_step: 1939, loss: 0.038151, Train_acc: 1.000000 Epoch:2, train_step: 1940, loss: 0.007599, Train_acc: 1.000000 Epoch:2, train_step: 1941, loss: 0.014950, Train_acc: 1.000000 Epoch:2, train_step: 1942, loss: 0.034491, Train_acc: 0.984375 Epoch:2, train_step: 1943, loss: 0.017359, Train_acc: 1.000000 Epoch:2, train_step: 1944, loss: 0.115730, Train_acc: 0.953125 Epoch:2, train_step: 1945, loss: 0.003030, Train_acc: 1.000000 Epoch:2, train_step: 1946, loss: 0.007972, Train_acc: 1.000000 Epoch:2, train_step: 1947, loss: 0.060925, Train_acc: 0.984375 Epoch:2, train_step: 1948, loss: 0.014182, Train_acc: 1.000000 Epoch:2, train_step: 1949, loss: 0.007987, Train_acc: 1.000000 Epoch:2, train_step: 1950, loss: 0.005862, Train_acc: 1.000000 Epoch:2, train_step: 1951, loss: 0.006742, Train_acc: 1.000000 Epoch:2, train_step: 1952, loss: 0.029709, Train_acc: 1.000000 Epoch:2, train_step: 1953, loss: 0.035035, Train_acc: 0.984375 Epoch:2, train_step: 1954, loss: 0.034334, Train_acc: 0.984375 Epoch:2, train_step: 1955, loss: 0.020659, Train_acc: 0.984375 Epoch:2, train_step: 1956, loss: 0.020259, Train_acc: 1.000000 Epoch:2, train_step: 1957, loss: 0.075307, Train_acc: 0.968750 Epoch:2, train_step: 1958, loss: 0.071030, Train_acc: 0.968750 Epoch:2, train_step: 1959, loss: 0.042257, Train_acc: 0.984375 Epoch:2, train_step: 1960, loss: 0.041502, Train_acc: 0.984375 Epoch:2, train_step: 1961, loss: 0.032381, Train_acc: 1.000000 Epoch:2, train_step: 1962, loss: 0.003026, Train_acc: 1.000000 Epoch:2, train_step: 1963, loss: 0.033610, Train_acc: 0.984375 Epoch:2, train_step: 1964, loss: 0.094408, Train_acc: 0.953125 Epoch:2, train_step: 1965, loss: 0.068125, Train_acc: 0.984375 Epoch:2, train_step: 1966, loss: 0.016874, Train_acc: 1.000000 Epoch:2, train_step: 1967, loss: 0.107194, Train_acc: 0.984375 Epoch:2, train_step: 1968, loss: 0.024507, Train_acc: 0.984375 Epoch:2, train_step: 1969, loss: 0.011205, Train_acc: 1.000000 Epoch:2, train_step: 1970, loss: 0.067888, Train_acc: 0.968750 Epoch:2, train_step: 1971, loss: 0.008421, Train_acc: 1.000000 Epoch:2, train_step: 1972, loss: 0.109069, Train_acc: 0.953125 Epoch:2, train_step: 1973, loss: 0.012134, Train_acc: 1.000000 Epoch:2, train_step: 1974, loss: 0.011197, Train_acc: 1.000000 Epoch:2, train_step: 1975, loss: 0.056652, Train_acc: 0.968750 Epoch:2, train_step: 1976, loss: 0.015081, Train_acc: 1.000000 Epoch:2, train_step: 1977, loss: 0.004361, Train_acc: 1.000000 Epoch:2, train_step: 1978, loss: 0.006617, Train_acc: 1.000000 Epoch:2, train_step: 1979, loss: 0.035826, Train_acc: 0.984375 Epoch:2, train_step: 1980, loss: 0.001655, Train_acc: 1.000000 Epoch:2, train_step: 1981, loss: 0.062475, Train_acc: 0.984375 Epoch:2, train_step: 1982, loss: 0.123699, Train_acc: 0.968750 Epoch:2, train_step: 1983, loss: 0.040849, Train_acc: 0.984375 Epoch:2, train_step: 1984, loss: 0.091525, Train_acc: 0.953125 Epoch:2, train_step: 1985, loss: 0.092456, Train_acc: 0.984375 Epoch:2, train_step: 1986, loss: 0.011818, Train_acc: 1.000000 Epoch:2, train_step: 1987, loss: 0.031945, Train_acc: 1.000000 Epoch:2, train_step: 1988, loss: 0.350314, Train_acc: 0.953125 Epoch:2, train_step: 1989, loss: 0.054617, Train_acc: 0.984375 Epoch:2, train_step: 1990, loss: 0.003764, Train_acc: 1.000000 Epoch:2, train_step: 1991, loss: 0.013595, Train_acc: 1.000000 Epoch:2, train_step: 1992, loss: 0.033049, Train_acc: 0.968750 Epoch:2, train_step: 1993, loss: 0.126700, Train_acc: 0.937500 Epoch:2, train_step: 1994, loss: 0.078696, Train_acc: 0.984375 Epoch:2, train_step: 1995, loss: 0.051058, Train_acc: 0.984375 Epoch:2, train_step: 1996, loss: 0.078381, Train_acc: 0.968750 Epoch:2, train_step: 1997, loss: 0.063603, Train_acc: 0.953125 Epoch:2, train_step: 1998, loss: 0.039955, Train_acc: 0.984375 Epoch:2, train_step: 1999, loss: 0.061709, Train_acc: 0.968750 Epoch:2, train_step: 2000, loss: 0.045900, Train_acc: 0.984375 Epoch:2, train_step: 2001, loss: 0.049694, Train_acc: 0.984375 Epoch:2, train_step: 2002, loss: 0.010235, Train_acc: 1.000000 Epoch:2, train_step: 2003, loss: 0.097039, Train_acc: 0.968750 Epoch:2, train_step: 2004, loss: 0.006470, Train_acc: 1.000000 Epoch:2, train_step: 2005, loss: 0.011139, Train_acc: 1.000000 Epoch:2, train_step: 2006, loss: 0.033205, Train_acc: 0.984375 Epoch:2, train_step: 2007, loss: 0.030921, Train_acc: 0.984375 Epoch:2, train_step: 2008, loss: 0.014707, Train_acc: 1.000000 Epoch:2, train_step: 2009, loss: 0.031981, Train_acc: 0.968750 Epoch:2, train_step: 2010, loss: 0.076742, Train_acc: 0.953125 Epoch:2, train_step: 2011, loss: 0.118447, Train_acc: 0.984375 Epoch:2, train_step: 2012, loss: 0.017620, Train_acc: 1.000000 Epoch:2, train_step: 2013, loss: 0.069114, Train_acc: 0.984375 Epoch:2, train_step: 2014, loss: 0.070084, Train_acc: 0.984375 Epoch:2, train_step: 2015, loss: 0.045349, Train_acc: 0.984375 Epoch:2, train_step: 2016, loss: 0.003880, Train_acc: 1.000000 Epoch:2, train_step: 2017, loss: 0.128304, Train_acc: 0.968750 Epoch:2, train_step: 2018, loss: 0.007553, Train_acc: 1.000000 Epoch:2, train_step: 2019, loss: 0.032588, Train_acc: 0.984375 Epoch:2, train_step: 2020, loss: 0.021483, Train_acc: 0.984375 Epoch:2, train_step: 2021, loss: 0.057080, Train_acc: 0.968750 Epoch:2, train_step: 2022, loss: 0.101699, Train_acc: 0.984375 Epoch:2, train_step: 2023, loss: 0.020939, Train_acc: 1.000000 Epoch:2, train_step: 2024, loss: 0.017526, Train_acc: 1.000000 Epoch:2, train_step: 2025, loss: 0.072281, Train_acc: 0.937500 Epoch:2, train_step: 2026, loss: 0.036673, Train_acc: 0.984375 Epoch:2, train_step: 2027, loss: 0.098097, Train_acc: 0.984375 Epoch:2, train_step: 2028, loss: 0.003325, Train_acc: 1.000000 Epoch:2, train_step: 2029, loss: 0.004074, Train_acc: 1.000000 Epoch:2, train_step: 2030, loss: 0.022157, Train_acc: 1.000000 Epoch:2, train_step: 2031, loss: 0.027402, Train_acc: 0.984375 Epoch:2, train_step: 2032, loss: 0.016414, Train_acc: 1.000000 Epoch:2, train_step: 2033, loss: 0.012525, Train_acc: 1.000000 Epoch:2, train_step: 2034, loss: 0.060635, Train_acc: 0.953125 Epoch:2, train_step: 2035, loss: 0.073965, Train_acc: 0.984375 Epoch:2, train_step: 2036, loss: 0.012491, Train_acc: 1.000000 Epoch:2, train_step: 2037, loss: 0.046705, Train_acc: 0.984375 Epoch:2, train_step: 2038, loss: 0.012270, Train_acc: 1.000000 Epoch:2, train_step: 2039, loss: 0.002187, Train_acc: 1.000000 Epoch:2, train_step: 2040, loss: 0.002655, Train_acc: 1.000000 Epoch:2, train_step: 2041, loss: 0.003142, Train_acc: 1.000000 Epoch:2, train_step: 2042, loss: 0.013128, Train_acc: 1.000000 Epoch:2, train_step: 2043, loss: 0.067231, Train_acc: 0.984375 Epoch:2, train_step: 2044, loss: 0.015661, Train_acc: 1.000000 Epoch:2, train_step: 2045, loss: 0.003068, Train_acc: 1.000000 Epoch:2, train_step: 2046, loss: 0.161746, Train_acc: 0.984375 Epoch:2, train_step: 2047, loss: 0.018186, Train_acc: 1.000000 Epoch:2, train_step: 2048, loss: 0.002479, Train_acc: 1.000000 Epoch:2, train_step: 2049, loss: 0.004785, Train_acc: 1.000000 Epoch:2, train_step: 2050, loss: 0.115502, Train_acc: 0.984375 Epoch:2, train_step: 2051, loss: 0.006856, Train_acc: 1.000000 Epoch:2, train_step: 2052, loss: 0.082288, Train_acc: 0.968750 Epoch:2, train_step: 2053, loss: 0.008120, Train_acc: 1.000000 Epoch:2, train_step: 2054, loss: 0.003927, Train_acc: 1.000000 Epoch:2, train_step: 2055, loss: 0.042386, Train_acc: 0.984375 Epoch:2, train_step: 2056, loss: 0.032038, Train_acc: 0.984375 Epoch:2, train_step: 2057, loss: 0.017274, Train_acc: 1.000000 Epoch:2, train_step: 2058, loss: 0.021630, Train_acc: 1.000000 Epoch:2, train_step: 2059, loss: 0.023256, Train_acc: 1.000000 Epoch:2, train_step: 2060, loss: 0.048114, Train_acc: 0.984375 Epoch:2, train_step: 2061, loss: 0.017068, Train_acc: 1.000000 Epoch:2, train_step: 2062, loss: 0.017057, Train_acc: 1.000000 Epoch:2, train_step: 2063, loss: 0.052848, Train_acc: 0.968750 Epoch:2, train_step: 2064, loss: 0.013523, Train_acc: 1.000000 Epoch:2, train_step: 2065, loss: 0.019472, Train_acc: 1.000000 Epoch:2, train_step: 2066, loss: 0.021377, Train_acc: 1.000000 Epoch:2, train_step: 2067, loss: 0.035684, Train_acc: 0.968750 Epoch:2, train_step: 2068, loss: 0.020607, Train_acc: 1.000000 Epoch:2, train_step: 2069, loss: 0.007959, Train_acc: 1.000000 Epoch:2, train_step: 2070, loss: 0.001045, Train_acc: 1.000000 Epoch:2, train_step: 2071, loss: 0.107369, Train_acc: 0.984375 Epoch:2, train_step: 2072, loss: 0.082577, Train_acc: 0.968750 Epoch:2, train_step: 2073, loss: 0.004552, Train_acc: 1.000000 Epoch:2, train_step: 2074, loss: 0.008570, Train_acc: 1.000000 Epoch:2, train_step: 2075, loss: 0.076581, Train_acc: 0.953125 Epoch:2, train_step: 2076, loss: 0.023094, Train_acc: 0.984375 Epoch:2, train_step: 2077, loss: 0.096560, Train_acc: 0.984375 Epoch:2, train_step: 2078, loss: 0.029286, Train_acc: 0.984375 Epoch:2, train_step: 2079, loss: 0.024043, Train_acc: 1.000000 Epoch:2, train_step: 2080, loss: 0.017620, Train_acc: 1.000000 Epoch:2, train_step: 2081, loss: 0.005837, Train_acc: 1.000000 Epoch:2, train_step: 2082, loss: 0.039588, Train_acc: 0.984375 Epoch:2, train_step: 2083, loss: 0.009814, Train_acc: 1.000000 Epoch:2, train_step: 2084, loss: 0.097833, Train_acc: 0.953125 Epoch:2, train_step: 2085, loss: 0.005705, Train_acc: 1.000000 Epoch:2, train_step: 2086, loss: 0.024912, Train_acc: 0.984375 Epoch:2, train_step: 2087, loss: 0.016925, Train_acc: 0.984375 Epoch:2, train_step: 2088, loss: 0.026775, Train_acc: 1.000000 Epoch:2, train_step: 2089, loss: 0.024954, Train_acc: 0.984375 Epoch:2, train_step: 2090, loss: 0.003312, Train_acc: 1.000000 Epoch:2, train_step: 2091, loss: 0.095640, Train_acc: 0.984375 Epoch:2, train_step: 2092, loss: 0.028967, Train_acc: 0.984375 Epoch:2, train_step: 2093, loss: 0.053197, Train_acc: 0.968750 Epoch:2, train_step: 2094, loss: 0.015483, Train_acc: 1.000000 Epoch:2, train_step: 2095, loss: 0.019107, Train_acc: 0.984375 Epoch:2, train_step: 2096, loss: 0.037446, Train_acc: 0.984375 Epoch:2, train_step: 2097, loss: 0.045168, Train_acc: 0.984375 Epoch:2, train_step: 2098, loss: 0.050584, Train_acc: 0.984375 Epoch:2, train_step: 2099, loss: 0.031693, Train_acc: 1.000000 Epoch:2, train_step: 2100, loss: 0.026199, Train_acc: 0.984375 Epoch:2, train_step: 2101, loss: 0.011252, Train_acc: 1.000000 Epoch:2, train_step: 2102, loss: 0.105662, Train_acc: 0.984375 Epoch:2, train_step: 2103, loss: 0.030527, Train_acc: 0.984375 Epoch:2, train_step: 2104, loss: 0.014048, Train_acc: 1.000000 Epoch:2, train_step: 2105, loss: 0.025645, Train_acc: 0.984375 Epoch:2, train_step: 2106, loss: 0.035837, Train_acc: 0.968750 Epoch:2, train_step: 2107, loss: 0.006304, Train_acc: 1.000000 Epoch:2, train_step: 2108, loss: 0.012658, Train_acc: 1.000000 Epoch:2, train_step: 2109, loss: 0.001421, Train_acc: 1.000000 Epoch:2, train_step: 2110, loss: 0.061716, Train_acc: 0.968750 Epoch:2, train_step: 2111, loss: 0.007471, Train_acc: 1.000000 Epoch:2, train_step: 2112, loss: 0.011171, Train_acc: 1.000000 Epoch:2, train_step: 2113, loss: 0.003866, Train_acc: 1.000000 Epoch:2, train_step: 2114, loss: 0.068676, Train_acc: 0.984375 Epoch:2, train_step: 2115, loss: 0.010875, Train_acc: 1.000000 Epoch:2, train_step: 2116, loss: 0.015376, Train_acc: 1.000000 Epoch:2, train_step: 2117, loss: 0.003531, Train_acc: 1.000000 Epoch:2, train_step: 2118, loss: 0.010646, Train_acc: 1.000000 Epoch:2, train_step: 2119, loss: 0.004322, Train_acc: 1.000000 Epoch:2, train_step: 2120, loss: 0.022460, Train_acc: 0.984375 Epoch:2, train_step: 2121, loss: 0.063857, Train_acc: 0.984375 Epoch:2, train_step: 2122, loss: 0.010664, Train_acc: 1.000000 Epoch:2, train_step: 2123, loss: 0.040211, Train_acc: 0.984375 Epoch:2, train_step: 2124, loss: 0.081792, Train_acc: 0.968750 Epoch:2, train_step: 2125, loss: 0.049593, Train_acc: 0.984375 Epoch:2, train_step: 2126, loss: 0.046912, Train_acc: 0.968750 Epoch:2, train_step: 2127, loss: 0.074782, Train_acc: 0.953125 Epoch:2, train_step: 2128, loss: 0.009954, Train_acc: 1.000000 Epoch:2, train_step: 2129, loss: 0.006214, Train_acc: 1.000000 Epoch:2, train_step: 2130, loss: 0.008588, Train_acc: 1.000000 Epoch:2, train_step: 2131, loss: 0.009964, Train_acc: 1.000000 Epoch:2, train_step: 2132, loss: 0.019154, Train_acc: 1.000000 Epoch:2, train_step: 2133, loss: 0.036303, Train_acc: 0.984375 Epoch:2, train_step: 2134, loss: 0.001744, Train_acc: 1.000000 Epoch:2, train_step: 2135, loss: 0.075836, Train_acc: 0.968750 Epoch:2, train_step: 2136, loss: 0.048116, Train_acc: 0.984375 Epoch:2, train_step: 2137, loss: 0.019638, Train_acc: 1.000000 Epoch:2, train_step: 2138, loss: 0.025167, Train_acc: 1.000000 Epoch:2, train_step: 2139, loss: 0.026914, Train_acc: 1.000000 Epoch:2, train_step: 2140, loss: 0.053209, Train_acc: 0.984375 Epoch:2, train_step: 2141, loss: 0.011643, Train_acc: 1.000000 Epoch:2, train_step: 2142, loss: 0.048237, Train_acc: 0.984375 Epoch:2, train_step: 2143, loss: 0.066174, Train_acc: 0.984375 Epoch:2, train_step: 2144, loss: 0.060244, Train_acc: 0.968750 Epoch:2, train_step: 2145, loss: 0.005860, Train_acc: 1.000000 Epoch:2, train_step: 2146, loss: 0.008588, Train_acc: 1.000000 Epoch:2, train_step: 2147, loss: 0.025841, Train_acc: 0.984375 Epoch:2, train_step: 2148, loss: 0.012693, Train_acc: 1.000000 Epoch:2, train_step: 2149, loss: 0.165367, Train_acc: 0.968750 Epoch:2, train_step: 2150, loss: 0.006508, Train_acc: 1.000000 Epoch:2, train_step: 2151, loss: 0.061622, Train_acc: 0.968750 Epoch:2, train_step: 2152, loss: 0.025944, Train_acc: 0.984375 Epoch:2, train_step: 2153, loss: 0.082919, Train_acc: 0.953125 Epoch:2, train_step: 2154, loss: 0.015023, Train_acc: 1.000000 Epoch:2, train_step: 2155, loss: 0.024200, Train_acc: 0.984375 Epoch:2, train_step: 2156, loss: 0.011153, Train_acc: 1.000000 Epoch:2, train_step: 2157, loss: 0.010630, Train_acc: 1.000000 Epoch:2, train_step: 2158, loss: 0.075184, Train_acc: 0.984375 Epoch:2, train_step: 2159, loss: 0.018815, Train_acc: 1.000000 Epoch:2, train_step: 2160, loss: 0.030952, Train_acc: 0.984375 Epoch:2, train_step: 2161, loss: 0.056841, Train_acc: 0.968750 Epoch:2, train_step: 2162, loss: 0.056688, Train_acc: 0.968750 Epoch:2, train_step: 2163, loss: 0.013655, Train_acc: 1.000000 Epoch:2, train_step: 2164, loss: 0.025092, Train_acc: 0.984375 Epoch:2, train_step: 2165, loss: 0.001752, Train_acc: 1.000000 Epoch:2, train_step: 2166, loss: 0.013465, Train_acc: 1.000000 Epoch:2, train_step: 2167, loss: 0.018498, Train_acc: 1.000000 Epoch:2, train_step: 2168, loss: 0.005948, Train_acc: 1.000000 Epoch:2, train_step: 2169, loss: 0.023577, Train_acc: 1.000000 Epoch:2, train_step: 2170, loss: 0.002748, Train_acc: 1.000000 Epoch:2, train_step: 2171, loss: 0.001610, Train_acc: 1.000000 Epoch:2, train_step: 2172, loss: 0.008632, Train_acc: 1.000000 Epoch:2, train_step: 2173, loss: 0.019065, Train_acc: 1.000000 Epoch:2, train_step: 2174, loss: 0.012110, Train_acc: 1.000000 Epoch:2, train_step: 2175, loss: 0.062887, Train_acc: 0.984375 Epoch:2, train_step: 2176, loss: 0.011544, Train_acc: 1.000000 Epoch:2, train_step: 2177, loss: 0.082400, Train_acc: 0.968750 Epoch:2, train_step: 2178, loss: 0.004700, Train_acc: 1.000000 Epoch:2, train_step: 2179, loss: 0.024026, Train_acc: 0.984375 Epoch:2, train_step: 2180, loss: 0.037146, Train_acc: 0.984375 Epoch:2, train_step: 2181, loss: 0.030049, Train_acc: 0.984375 Epoch:2, train_step: 2182, loss: 0.002861, Train_acc: 1.000000 Epoch:2, train_step: 2183, loss: 0.006392, Train_acc: 1.000000 Epoch:2, train_step: 2184, loss: 0.001876, Train_acc: 1.000000 Epoch:2, train_step: 2185, loss: 0.062553, Train_acc: 0.968750 Epoch:2, train_step: 2186, loss: 0.020015, Train_acc: 0.984375 Epoch:2, train_step: 2187, loss: 0.019786, Train_acc: 0.984375 Epoch:2, train_step: 2188, loss: 0.049918, Train_acc: 0.984375 Epoch:2, train_step: 2189, loss: 0.020677, Train_acc: 1.000000 Epoch:2, train_step: 2190, loss: 0.027264, Train_acc: 1.000000 Epoch:2, train_step: 2191, loss: 0.015914, Train_acc: 1.000000 Epoch:2, train_step: 2192, loss: 0.009517, Train_acc: 1.000000 Epoch:2, train_step: 2193, loss: 0.005782, Train_acc: 1.000000 Epoch:2, train_step: 2194, loss: 0.013477, Train_acc: 1.000000 Epoch:2, train_step: 2195, loss: 0.005426, Train_acc: 1.000000 Epoch:2, train_step: 2196, loss: 0.020037, Train_acc: 0.984375 Epoch:2, train_step: 2197, loss: 0.043834, Train_acc: 0.984375 Epoch:2, train_step: 2198, loss: 0.012451, Train_acc: 1.000000 Epoch:2, train_step: 2199, loss: 0.131394, Train_acc: 0.968750 Epoch:2, train_step: 2200, loss: 0.044517, Train_acc: 0.968750 Epoch:2, train_step: 2201, loss: 0.012404, Train_acc: 1.000000 Epoch:2, train_step: 2202, loss: 0.004508, Train_acc: 1.000000 Epoch:2, train_step: 2203, loss: 0.004121, Train_acc: 1.000000 Epoch:2, train_step: 2204, loss: 0.002003, Train_acc: 1.000000 Epoch:2, train_step: 2205, loss: 0.078955, Train_acc: 0.968750 Epoch:2, train_step: 2206, loss: 0.015192, Train_acc: 0.984375 Epoch:2, train_step: 2207, loss: 0.009858, Train_acc: 1.000000 Epoch:2, train_step: 2208, loss: 0.030541, Train_acc: 0.984375 Epoch:2, train_step: 2209, loss: 0.019487, Train_acc: 1.000000 Epoch:2, train_step: 2210, loss: 0.052291, Train_acc: 0.984375 Epoch:2, train_step: 2211, loss: 0.006401, Train_acc: 1.000000 Epoch:2, train_step: 2212, loss: 0.022911, Train_acc: 0.984375 Epoch:2, train_step: 2213, loss: 0.031019, Train_acc: 0.984375 Epoch:2, train_step: 2214, loss: 0.002999, Train_acc: 1.000000 Epoch:2, train_step: 2215, loss: 0.031244, Train_acc: 0.984375 Epoch:2, train_step: 2216, loss: 0.006219, Train_acc: 1.000000 Epoch:2, train_step: 2217, loss: 0.017214, Train_acc: 1.000000 Epoch:2, train_step: 2218, loss: 0.019578, Train_acc: 1.000000 Epoch:2, train_step: 2219, loss: 0.011383, Train_acc: 1.000000 Epoch:2, train_step: 2220, loss: 0.018932, Train_acc: 1.000000 Epoch:2, train_step: 2221, loss: 0.026691, Train_acc: 0.984375 Epoch:2, train_step: 2222, loss: 0.016168, Train_acc: 1.000000 Epoch:2, train_step: 2223, loss: 0.050678, Train_acc: 0.968750 Epoch:2, train_step: 2224, loss: 0.008171, Train_acc: 1.000000 Epoch:2, train_step: 2225, loss: 0.007429, Train_acc: 1.000000 Epoch:2, train_step: 2226, loss: 0.011145, Train_acc: 1.000000 Epoch:2, train_step: 2227, loss: 0.020088, Train_acc: 1.000000 Epoch:2, train_step: 2228, loss: 0.029734, Train_acc: 0.984375 Epoch:2, train_step: 2229, loss: 0.030295, Train_acc: 0.984375 Epoch:2, train_step: 2230, loss: 0.028044, Train_acc: 0.984375 Epoch:2, train_step: 2231, loss: 0.014607, Train_acc: 1.000000 Epoch:2, train_step: 2232, loss: 0.028676, Train_acc: 0.984375 Epoch:2, train_step: 2233, loss: 0.000889, Train_acc: 1.000000 Epoch:2, train_step: 2234, loss: 0.005571, Train_acc: 1.000000 Epoch:2, train_step: 2235, loss: 0.017445, Train_acc: 1.000000 Epoch:2, train_step: 2236, loss: 0.009694, Train_acc: 1.000000 Epoch:2, train_step: 2237, loss: 0.004720, Train_acc: 1.000000 Epoch:2, train_step: 2238, loss: 0.004103, Train_acc: 1.000000 Epoch:2, train_step: 2239, loss: 0.001421, Train_acc: 1.000000 Epoch:2, train_step: 2240, loss: 0.004366, Train_acc: 1.000000 Epoch:2, train_step: 2241, loss: 0.007367, Train_acc: 1.000000 Epoch:2, train_step: 2242, loss: 0.003370, Train_acc: 1.000000 Epoch:2, train_step: 2243, loss: 0.062470, Train_acc: 0.984375 Epoch:2, train_step: 2244, loss: 0.030789, Train_acc: 0.984375 Epoch:2, train_step: 2245, loss: 0.011704, Train_acc: 1.000000 Epoch:2, train_step: 2246, loss: 0.006652, Train_acc: 1.000000 Epoch:2, train_step: 2247, loss: 0.095488, Train_acc: 0.984375 Epoch:2, train_step: 2248, loss: 0.105594, Train_acc: 0.984375 Epoch:2, train_step: 2249, loss: 0.030539, Train_acc: 0.984375 Epoch:2, train_step: 2250, loss: 0.006441, Train_acc: 1.000000 Epoch:2, train_step: 2251, loss: 0.023888, Train_acc: 0.984375 Epoch:2, train_step: 2252, loss: 0.005040, Train_acc: 1.000000 Epoch:2, train_step: 2253, loss: 0.013289, Train_acc: 1.000000 Epoch:2, train_step: 2254, loss: 0.015421, Train_acc: 1.000000 Epoch:2, train_step: 2255, loss: 0.000859, Train_acc: 1.000000 Epoch:2, train_step: 2256, loss: 0.005498, Train_acc: 1.000000 Epoch:2, train_step: 2257, loss: 0.007127, Train_acc: 1.000000 Epoch:2, train_step: 2258, loss: 0.023416, Train_acc: 0.984375 Epoch:2, train_step: 2259, loss: 0.027356, Train_acc: 0.984375 Epoch:2, train_step: 2260, loss: 0.031987, Train_acc: 0.984375 Epoch:2, train_step: 2261, loss: 0.008235, Train_acc: 1.000000 Epoch:2, train_step: 2262, loss: 0.070538, Train_acc: 0.984375 Epoch:2, train_step: 2263, loss: 0.017186, Train_acc: 0.984375 Epoch:2, train_step: 2264, loss: 0.006489, Train_acc: 1.000000 Epoch:2, train_step: 2265, loss: 0.007782, Train_acc: 1.000000 Epoch:2, train_step: 2266, loss: 0.003209, Train_acc: 1.000000 Epoch:2, train_step: 2267, loss: 0.035253, Train_acc: 0.984375 Epoch:2, train_step: 2268, loss: 0.044656, Train_acc: 0.984375 Epoch:2, train_step: 2269, loss: 0.010705, Train_acc: 1.000000 Epoch:2, train_step: 2270, loss: 0.006279, Train_acc: 1.000000 Epoch:2, train_step: 2271, loss: 0.002803, Train_acc: 1.000000 Epoch:2, train_step: 2272, loss: 0.000933, Train_acc: 1.000000 Epoch:2, train_step: 2273, loss: 0.025096, Train_acc: 1.000000 Epoch:2, train_step: 2274, loss: 0.067139, Train_acc: 0.968750 Epoch:2, train_step: 2275, loss: 0.014435, Train_acc: 0.984375 Epoch:2, train_step: 2276, loss: 0.068393, Train_acc: 0.984375 Epoch:2, train_step: 2277, loss: 0.049259, Train_acc: 0.984375 Epoch:2, train_step: 2278, loss: 0.080687, Train_acc: 0.968750 Epoch:2, train_step: 2279, loss: 0.026285, Train_acc: 0.984375 Epoch:2, train_step: 2280, loss: 0.010396, Train_acc: 1.000000 Epoch:2, train_step: 2281, loss: 0.083986, Train_acc: 0.984375 Epoch:2, train_step: 2282, loss: 0.018672, Train_acc: 0.984375 Epoch:2, train_step: 2283, loss: 0.007401, Train_acc: 1.000000 Epoch:2, train_step: 2284, loss: 0.071019, Train_acc: 0.984375 Epoch:2, train_step: 2285, loss: 0.012770, Train_acc: 1.000000 Epoch:2, train_step: 2286, loss: 0.019663, Train_acc: 0.984375 Epoch:2, train_step: 2287, loss: 0.070968, Train_acc: 0.968750 Epoch:2, train_step: 2288, loss: 0.041648, Train_acc: 0.968750 Epoch:2, train_step: 2289, loss: 0.119142, Train_acc: 0.953125 Epoch:2, train_step: 2290, loss: 0.168403, Train_acc: 0.968750 Epoch:2, train_step: 2291, loss: 0.168947, Train_acc: 0.968750 Epoch:2, train_step: 2292, loss: 0.097753, Train_acc: 0.968750 Epoch:2, train_step: 2293, loss: 0.042911, Train_acc: 0.968750 Epoch:2, train_step: 2294, loss: 0.097552, Train_acc: 0.953125 Epoch:2, train_step: 2295, loss: 0.117873, Train_acc: 0.968750 Epoch:2, train_step: 2296, loss: 0.014414, Train_acc: 0.984375 Epoch:2, train_step: 2297, loss: 0.006974, Train_acc: 1.000000 Epoch:2, train_step: 2298, loss: 0.011496, Train_acc: 1.000000 Epoch:2, train_step: 2299, loss: 0.079264, Train_acc: 0.968750 Epoch:2, train_step: 2300, loss: 0.072446, Train_acc: 0.968750 Epoch:2, train_step: 2301, loss: 0.010106, Train_acc: 1.000000 Epoch:2, train_step: 2302, loss: 0.002055, Train_acc: 1.000000 Epoch:2, train_step: 2303, loss: 0.015216, Train_acc: 1.000000 Epoch:2, train_step: 2304, loss: 0.078255, Train_acc: 0.984375 Epoch:2, train_step: 2305, loss: 0.012415, Train_acc: 1.000000 Epoch:2, train_step: 2306, loss: 0.078667, Train_acc: 0.968750 Epoch:2, train_step: 2307, loss: 0.028669, Train_acc: 1.000000 Epoch:2, train_step: 2308, loss: 0.006591, Train_acc: 1.000000 Epoch:2, train_step: 2309, loss: 0.011578, Train_acc: 1.000000 Epoch:2, train_step: 2310, loss: 0.075074, Train_acc: 0.984375 Epoch:2, train_step: 2311, loss: 0.003030, Train_acc: 1.000000 Epoch:2, train_step: 2312, loss: 0.088226, Train_acc: 0.984375 Epoch:2, train_step: 2313, loss: 0.000650, Train_acc: 1.000000 Epoch:2, train_step: 2314, loss: 0.006414, Train_acc: 1.000000 Epoch:2, train_step: 2315, loss: 0.009596, Train_acc: 1.000000 Epoch:2, train_step: 2316, loss: 0.013230, Train_acc: 1.000000 Epoch:2, train_step: 2317, loss: 0.013724, Train_acc: 0.984375 Epoch:2, train_step: 2318, loss: 0.047431, Train_acc: 0.984375 Epoch:2, train_step: 2319, loss: 0.011152, Train_acc: 1.000000 Epoch:2, train_step: 2320, loss: 0.074791, Train_acc: 0.984375 Epoch:2, train_step: 2321, loss: 0.005094, Train_acc: 1.000000 Epoch:2, train_step: 2322, loss: 0.097863, Train_acc: 0.968750 Epoch:2, train_step: 2323, loss: 0.154822, Train_acc: 0.968750 Epoch:2, train_step: 2324, loss: 0.011731, Train_acc: 1.000000 Epoch:2, train_step: 2325, loss: 0.013526, Train_acc: 1.000000 Epoch:2, train_step: 2326, loss: 0.005037, Train_acc: 1.000000 Epoch:2, train_step: 2327, loss: 0.006387, Train_acc: 1.000000 Epoch:2, train_step: 2328, loss: 0.032149, Train_acc: 0.968750 Epoch:2, train_step: 2329, loss: 0.020645, Train_acc: 0.984375 Epoch:2, train_step: 2330, loss: 0.029897, Train_acc: 1.000000 Epoch:2, train_step: 2331, loss: 0.031228, Train_acc: 0.984375 Epoch:2, train_step: 2332, loss: 0.035745, Train_acc: 0.984375 Epoch:2, train_step: 2333, loss: 0.004695, Train_acc: 1.000000 Epoch:2, train_step: 2334, loss: 0.008098, Train_acc: 1.000000 Epoch:2, train_step: 2335, loss: 0.035862, Train_acc: 0.984375 Epoch:2, train_step: 2336, loss: 0.003242, Train_acc: 1.000000 Epoch:2, train_step: 2337, loss: 0.048965, Train_acc: 0.984375 Epoch:2, train_step: 2338, loss: 0.002589, Train_acc: 1.000000 Epoch:2, train_step: 2339, loss: 0.045769, Train_acc: 0.984375 Epoch:2, train_step: 2340, loss: 0.005803, Train_acc: 1.000000 Epoch:2, train_step: 2341, loss: 0.012493, Train_acc: 1.000000 Epoch:2, train_step: 2342, loss: 0.011857, Train_acc: 1.000000 Epoch:2, train_step: 2343, loss: 0.005584, Train_acc: 1.000000 Epoch:2, train_step: 2344, loss: 0.021927, Train_acc: 0.984375 Epoch:2, train_step: 2345, loss: 0.049026, Train_acc: 0.984375 Epoch:2, train_step: 2346, loss: 0.017504, Train_acc: 1.000000 Epoch:2, train_step: 2347, loss: 0.006584, Train_acc: 1.000000 Epoch:2, train_step: 2348, loss: 0.019719, Train_acc: 0.984375 Epoch:2, train_step: 2349, loss: 0.026558, Train_acc: 0.984375 Epoch:2, train_step: 2350, loss: 0.004691, Train_acc: 1.000000 Epoch:2, train_step: 2351, loss: 0.023035, Train_acc: 1.000000 Epoch:2, train_step: 2352, loss: 0.004232, Train_acc: 1.000000 Epoch:2, train_step: 2353, loss: 0.109883, Train_acc: 0.968750 Epoch:2, train_step: 2354, loss: 0.011228, Train_acc: 1.000000 Epoch:2, train_step: 2355, loss: 0.013183, Train_acc: 1.000000 Epoch:2, train_step: 2356, loss: 0.058727, Train_acc: 0.968750 Epoch:2, train_step: 2357, loss: 0.011838, Train_acc: 1.000000 Epoch:2, train_step: 2358, loss: 0.035774, Train_acc: 0.984375 Epoch:2, train_step: 2359, loss: 0.003005, Train_acc: 1.000000 Epoch:2, train_step: 2360, loss: 0.016232, Train_acc: 1.000000 Epoch:2, train_step: 2361, loss: 0.006395, Train_acc: 1.000000 Epoch:2, train_step: 2362, loss: 0.021697, Train_acc: 1.000000 Epoch:2, train_step: 2363, loss: 0.013275, Train_acc: 1.000000 Epoch:2, train_step: 2364, loss: 0.011093, Train_acc: 1.000000 Epoch:2, train_step: 2365, loss: 0.020400, Train_acc: 1.000000 Epoch:2, train_step: 2366, loss: 0.003776, Train_acc: 1.000000 Epoch:2, train_step: 2367, loss: 0.054985, Train_acc: 0.968750 Epoch:2, train_step: 2368, loss: 0.052541, Train_acc: 0.984375 Epoch:2, train_step: 2369, loss: 0.113277, Train_acc: 0.953125 Epoch:2, train_step: 2370, loss: 0.067322, Train_acc: 0.984375 Epoch:2, train_step: 2371, loss: 0.014938, Train_acc: 0.984375 Epoch:2, train_step: 2372, loss: 0.085828, Train_acc: 0.953125 Epoch:2, train_step: 2373, loss: 0.002327, Train_acc: 1.000000 Epoch:2, train_step: 2374, loss: 0.041338, Train_acc: 0.984375 Epoch:2, train_step: 2375, loss: 0.028908, Train_acc: 0.984375 Epoch:2, train_step: 2376, loss: 0.113914, Train_acc: 0.984375 Epoch:2, train_step: 2377, loss: 0.018130, Train_acc: 1.000000 Epoch:2, train_step: 2378, loss: 0.007751, Train_acc: 1.000000 Epoch:2, train_step: 2379, loss: 0.006112, Train_acc: 1.000000 Epoch:2, train_step: 2380, loss: 0.301816, Train_acc: 0.953125 Epoch:2, train_step: 2381, loss: 0.029056, Train_acc: 0.984375 Epoch:2, train_step: 2382, loss: 0.041877, Train_acc: 0.984375 Epoch:2, train_step: 2383, loss: 0.032831, Train_acc: 0.984375 Epoch:2, train_step: 2384, loss: 0.002520, Train_acc: 1.000000 Epoch:2, train_step: 2385, loss: 0.029623, Train_acc: 0.984375 Epoch:2, train_step: 2386, loss: 0.052974, Train_acc: 0.984375 Epoch:2, train_step: 2387, loss: 0.004922, Train_acc: 1.000000 Epoch:2, train_step: 2388, loss: 0.024635, Train_acc: 0.984375 Epoch:2, train_step: 2389, loss: 0.013678, Train_acc: 1.000000 Epoch:2, train_step: 2390, loss: 0.003298, Train_acc: 1.000000 Epoch:2, train_step: 2391, loss: 0.017502, Train_acc: 1.000000 Epoch:2, train_step: 2392, loss: 0.007683, Train_acc: 1.000000 Epoch:2, train_step: 2393, loss: 0.009726, Train_acc: 1.000000 Epoch:2, train_step: 2394, loss: 0.041403, Train_acc: 0.968750 Epoch:2, train_step: 2395, loss: 0.023218, Train_acc: 1.000000 Epoch:2, train_step: 2396, loss: 0.011823, Train_acc: 1.000000 Epoch:2, train_step: 2397, loss: 0.027748, Train_acc: 0.984375 Epoch:2, train_step: 2398, loss: 0.013901, Train_acc: 1.000000 Epoch:2, train_step: 2399, loss: 0.017396, Train_acc: 0.984375 Epoch:2, train_step: 2400, loss: 0.026514, Train_acc: 1.000000 Epoch:2, train_step: 2401, loss: 0.005839, Train_acc: 1.000000 Epoch:2, train_step: 2402, loss: 0.093334, Train_acc: 0.984375 Epoch:2, train_step: 2403, loss: 0.008875, Train_acc: 1.000000 Epoch:2, train_step: 2404, loss: 0.001540, Train_acc: 1.000000 Epoch:2, train_step: 2405, loss: 0.000935, Train_acc: 1.000000 Epoch:2, train_step: 2406, loss: 0.004943, Train_acc: 1.000000 Epoch:2, train_step: 2407, loss: 0.034439, Train_acc: 0.984375 Epoch:2, train_step: 2408, loss: 0.037071, Train_acc: 0.984375 Epoch:2, train_step: 2409, loss: 0.005398, Train_acc: 1.000000 Epoch:2, train_step: 2410, loss: 0.000515, Train_acc: 1.000000 Epoch:2, train_step: 2411, loss: 0.023056, Train_acc: 0.984375 Epoch:2, train_step: 2412, loss: 0.161845, Train_acc: 0.984375 Epoch:2, train_step: 2413, loss: 0.011679, Train_acc: 1.000000 Epoch:2, train_step: 2414, loss: 0.005977, Train_acc: 1.000000 Epoch:2, train_step: 2415, loss: 0.006437, Train_acc: 1.000000 Epoch:2, train_step: 2416, loss: 0.119569, Train_acc: 0.937500 Epoch:2, train_step: 2417, loss: 0.158484, Train_acc: 0.968750 Epoch:2, train_step: 2418, loss: 0.030655, Train_acc: 0.984375 Epoch:2, train_step: 2419, loss: 0.128647, Train_acc: 0.937500 Epoch:2, train_step: 2420, loss: 0.098189, Train_acc: 0.984375 Epoch:2, train_step: 2421, loss: 0.005325, Train_acc: 1.000000 Epoch:2, train_step: 2422, loss: 0.068156, Train_acc: 0.953125 Epoch:2, train_step: 2423, loss: 0.003033, Train_acc: 1.000000 Epoch:2, train_step: 2424, loss: 0.088872, Train_acc: 0.984375 Epoch:2, train_step: 2425, loss: 0.127951, Train_acc: 0.968750 Epoch:2, train_step: 2426, loss: 0.064256, Train_acc: 0.968750 Epoch:2, train_step: 2427, loss: 0.022470, Train_acc: 1.000000 Epoch:2, train_step: 2428, loss: 0.031693, Train_acc: 0.984375 Epoch:2, train_step: 2429, loss: 0.143874, Train_acc: 0.968750 Epoch:2, train_step: 2430, loss: 0.026094, Train_acc: 0.984375 Epoch:2, train_step: 2431, loss: 0.088882, Train_acc: 0.984375 Epoch:2, train_step: 2432, loss: 0.010972, Train_acc: 1.000000 Epoch:2, train_step: 2433, loss: 0.047309, Train_acc: 0.984375 Epoch:2, train_step: 2434, loss: 0.001892, Train_acc: 1.000000 Epoch:2, train_step: 2435, loss: 0.008199, Train_acc: 1.000000 Epoch:2, train_step: 2436, loss: 0.021777, Train_acc: 1.000000 Epoch:2, train_step: 2437, loss: 0.053471, Train_acc: 0.968750 Epoch:2, train_step: 2438, loss: 0.005449, Train_acc: 1.000000 Epoch:2, train_step: 2439, loss: 0.062856, Train_acc: 0.984375 Epoch:2, train_step: 2440, loss: 0.095536, Train_acc: 0.968750 Epoch:2, train_step: 2441, loss: 0.009412, Train_acc: 1.000000 Epoch:2, train_step: 2442, loss: 0.001854, Train_acc: 1.000000 Epoch:2, train_step: 2443, loss: 0.008697, Train_acc: 1.000000 Epoch:2, train_step: 2444, loss: 0.123273, Train_acc: 0.984375 Epoch:2, train_step: 2445, loss: 0.006557, Train_acc: 1.000000 Epoch:2, train_step: 2446, loss: 0.002132, Train_acc: 1.000000 Epoch:2, train_step: 2447, loss: 0.023955, Train_acc: 0.984375 Epoch:2, train_step: 2448, loss: 0.107971, Train_acc: 0.953125 Epoch:2, train_step: 2449, loss: 0.055454, Train_acc: 0.984375 Epoch:2, train_step: 2450, loss: 0.027797, Train_acc: 0.984375 Epoch:2, train_step: 2451, loss: 0.003706, Train_acc: 1.000000 Epoch:2, train_step: 2452, loss: 0.055545, Train_acc: 0.984375 Epoch:2, train_step: 2453, loss: 0.132449, Train_acc: 0.984375 Epoch:2, train_step: 2454, loss: 0.030769, Train_acc: 0.984375 Epoch:2, train_step: 2455, loss: 0.061824, Train_acc: 0.968750 Epoch:2, train_step: 2456, loss: 0.009722, Train_acc: 1.000000 Epoch:2, train_step: 2457, loss: 0.013868, Train_acc: 0.984375 Epoch:2, train_step: 2458, loss: 0.005046, Train_acc: 1.000000 Epoch:2, train_step: 2459, loss: 0.095501, Train_acc: 0.968750 Epoch:2, train_step: 2460, loss: 0.022557, Train_acc: 0.984375 Epoch:2, train_step: 2461, loss: 0.008726, Train_acc: 1.000000 Epoch:2, train_step: 2462, loss: 0.008164, Train_acc: 1.000000 Epoch:2, train_step: 2463, loss: 0.036202, Train_acc: 0.984375 Epoch:2, train_step: 2464, loss: 0.043291, Train_acc: 0.984375 Epoch:2, train_step: 2465, loss: 0.034507, Train_acc: 0.984375 Epoch:2, train_step: 2466, loss: 0.098885, Train_acc: 0.968750 Epoch:2, train_step: 2467, loss: 0.007771, Train_acc: 1.000000 Epoch:2, train_step: 2468, loss: 0.012090, Train_acc: 1.000000 Epoch:2, train_step: 2469, loss: 0.005137, Train_acc: 1.000000 Epoch:2, train_step: 2470, loss: 0.009411, Train_acc: 1.000000 Epoch:2, train_step: 2471, loss: 0.037214, Train_acc: 0.984375 Epoch:2, train_step: 2472, loss: 0.012879, Train_acc: 1.000000 Epoch:2, train_step: 2473, loss: 0.012597, Train_acc: 1.000000 Epoch:2, train_step: 2474, loss: 0.035380, Train_acc: 0.968750 Epoch:2, train_step: 2475, loss: 0.064066, Train_acc: 0.984375 Epoch:2, train_step: 2476, loss: 0.051450, Train_acc: 0.984375 Epoch:2, train_step: 2477, loss: 0.004844, Train_acc: 1.000000 Epoch:2, train_step: 2478, loss: 0.042246, Train_acc: 0.984375 Epoch:2, train_step: 2479, loss: 0.124141, Train_acc: 0.984375 Epoch:2, train_step: 2480, loss: 0.038455, Train_acc: 0.984375 Epoch:2, train_step: 2481, loss: 0.007163, Train_acc: 1.000000 Epoch:2, train_step: 2482, loss: 0.020891, Train_acc: 0.984375 Epoch:2, train_step: 2483, loss: 0.006409, Train_acc: 1.000000 Epoch:2, train_step: 2484, loss: 0.019828, Train_acc: 1.000000 Epoch:2, train_step: 2485, loss: 0.001327, Train_acc: 1.000000 Epoch:2, train_step: 2486, loss: 0.002159, Train_acc: 1.000000 Epoch:2, train_step: 2487, loss: 0.029291, Train_acc: 0.984375 Epoch:2, train_step: 2488, loss: 0.112395, Train_acc: 0.953125 Epoch:2, train_step: 2489, loss: 0.102194, Train_acc: 0.968750 Epoch:2, train_step: 2490, loss: 0.082134, Train_acc: 0.968750 Epoch:2, train_step: 2491, loss: 0.025822, Train_acc: 0.984375 Epoch:2, train_step: 2492, loss: 0.017694, Train_acc: 1.000000 Epoch:2, train_step: 2493, loss: 0.013272, Train_acc: 1.000000 Epoch:2, train_step: 2494, loss: 0.050431, Train_acc: 0.984375 Epoch:2, train_step: 2495, loss: 0.028769, Train_acc: 0.984375 Epoch:2, train_step: 2496, loss: 0.041791, Train_acc: 0.984375 Epoch:2, train_step: 2497, loss: 0.056138, Train_acc: 0.968750 Epoch:2, train_step: 2498, loss: 0.010677, Train_acc: 1.000000 Epoch:2, train_step: 2499, loss: 0.032177, Train_acc: 0.984375 Epoch:2, train_step: 2500, loss: 0.051756, Train_acc: 0.984375 Epoch:2, train_step: 2501, loss: 0.033627, Train_acc: 0.984375 Epoch:2, train_step: 2502, loss: 0.177598, Train_acc: 0.984375 Epoch:2, train_step: 2503, loss: 0.016801, Train_acc: 0.984375 Epoch:2, train_step: 2504, loss: 0.073671, Train_acc: 0.968750 Epoch:2, train_step: 2505, loss: 0.042002, Train_acc: 0.984375 Epoch:2, train_step: 2506, loss: 0.048150, Train_acc: 0.984375 Epoch:2, train_step: 2507, loss: 0.003300, Train_acc: 1.000000 Epoch:2, train_step: 2508, loss: 0.058914, Train_acc: 0.968750 Epoch:2, train_step: 2509, loss: 0.029568, Train_acc: 0.984375 Epoch:2, train_step: 2510, loss: 0.026865, Train_acc: 0.984375 Epoch:2, train_step: 2511, loss: 0.063492, Train_acc: 0.968750 Epoch:2, train_step: 2512, loss: 0.005074, Train_acc: 1.000000 Epoch:2, train_step: 2513, loss: 0.046090, Train_acc: 0.984375 Epoch:2, train_step: 2514, loss: 0.051701, Train_acc: 0.984375 Epoch:2, train_step: 2515, loss: 0.067388, Train_acc: 0.984375 Epoch:2, train_step: 2516, loss: 0.038686, Train_acc: 0.984375 Epoch:2, train_step: 2517, loss: 0.003640, Train_acc: 1.000000 Epoch:2, train_step: 2518, loss: 0.020864, Train_acc: 0.984375 Epoch:2, train_step: 2519, loss: 0.069024, Train_acc: 0.953125 Epoch:2, train_step: 2520, loss: 0.074183, Train_acc: 0.984375 Epoch:2, train_step: 2521, loss: 0.094992, Train_acc: 0.968750 Epoch:2, train_step: 2522, loss: 0.019543, Train_acc: 1.000000 Epoch:2, train_step: 2523, loss: 0.017636, Train_acc: 1.000000 Epoch:2, train_step: 2524, loss: 0.034784, Train_acc: 0.984375 Epoch:2, train_step: 2525, loss: 0.082828, Train_acc: 0.984375 Epoch:2, train_step: 2526, loss: 0.006827, Train_acc: 1.000000 Epoch:2, train_step: 2527, loss: 0.076895, Train_acc: 0.953125 Epoch:2, train_step: 2528, loss: 0.012740, Train_acc: 1.000000 Epoch:2, train_step: 2529, loss: 0.088761, Train_acc: 0.953125 Epoch:2, train_step: 2530, loss: 0.003791, Train_acc: 1.000000 Epoch:2, train_step: 2531, loss: 0.046592, Train_acc: 0.968750 Epoch:2, train_step: 2532, loss: 0.015619, Train_acc: 0.984375 Epoch:2, train_step: 2533, loss: 0.008767, Train_acc: 1.000000 Epoch:2, train_step: 2534, loss: 0.005370, Train_acc: 1.000000 Epoch:2, train_step: 2535, loss: 0.003399, Train_acc: 1.000000 Epoch:2, train_step: 2536, loss: 0.041327, Train_acc: 0.984375 Epoch:2, train_step: 2537, loss: 0.014516, Train_acc: 1.000000 Epoch:2, train_step: 2538, loss: 0.075961, Train_acc: 0.984375 Epoch:2, train_step: 2539, loss: 0.004205, Train_acc: 1.000000 Epoch:2, train_step: 2540, loss: 0.090804, Train_acc: 0.984375 Epoch:2, train_step: 2541, loss: 0.047954, Train_acc: 0.984375 Epoch:2, train_step: 2542, loss: 0.015332, Train_acc: 1.000000 Epoch:2, train_step: 2543, loss: 0.010219, Train_acc: 1.000000 Epoch:2, train_step: 2544, loss: 0.042377, Train_acc: 0.984375 Epoch:2, train_step: 2545, loss: 0.014978, Train_acc: 1.000000 Epoch:2, train_step: 2546, loss: 0.048495, Train_acc: 0.984375 Epoch:2, train_step: 2547, loss: 0.071323, Train_acc: 0.968750 Epoch:2, train_step: 2548, loss: 0.186944, Train_acc: 0.984375 Epoch:2, train_step: 2549, loss: 0.015164, Train_acc: 1.000000 Epoch:2, train_step: 2550, loss: 0.006798, Train_acc: 1.000000 Epoch:2, train_step: 2551, loss: 0.003291, Train_acc: 1.000000 Epoch:2, train_step: 2552, loss: 0.004289, Train_acc: 1.000000 Epoch:2, train_step: 2553, loss: 0.154319, Train_acc: 0.984375 Epoch:2, train_step: 2554, loss: 0.018973, Train_acc: 0.984375 Epoch:2, train_step: 2555, loss: 0.048847, Train_acc: 0.984375 Epoch:2, train_step: 2556, loss: 0.019871, Train_acc: 0.984375 Epoch:2, train_step: 2557, loss: 0.141337, Train_acc: 0.968750 Epoch:2, train_step: 2558, loss: 0.005861, Train_acc: 1.000000 Epoch:2, train_step: 2559, loss: 0.003575, Train_acc: 1.000000 Epoch:2, train_step: 2560, loss: 0.019191, Train_acc: 1.000000 Epoch:2, train_step: 2561, loss: 0.015047, Train_acc: 1.000000 Epoch:2, train_step: 2562, loss: 0.009504, Train_acc: 1.000000 Epoch:2, train_step: 2563, loss: 0.038401, Train_acc: 0.984375 Epoch:2, train_step: 2564, loss: 0.007301, Train_acc: 1.000000 Epoch:2, train_step: 2565, loss: 0.007927, Train_acc: 1.000000 Epoch:2, train_step: 2566, loss: 0.053148, Train_acc: 0.984375 Epoch:2, train_step: 2567, loss: 0.008893, Train_acc: 1.000000 Epoch:2, train_step: 2568, loss: 0.006031, Train_acc: 1.000000 Epoch:2, train_step: 2569, loss: 0.069459, Train_acc: 0.953125 Epoch:2, train_step: 2570, loss: 0.015586, Train_acc: 1.000000 Epoch:2, train_step: 2571, loss: 0.002054, Train_acc: 1.000000 Epoch:2, train_step: 2572, loss: 0.002913, Train_acc: 1.000000 Epoch:2, train_step: 2573, loss: 0.003656, Train_acc: 1.000000 Epoch:2, train_step: 2574, loss: 0.009942, Train_acc: 1.000000 Epoch:2, train_step: 2575, loss: 0.027948, Train_acc: 1.000000 Epoch:2, train_step: 2576, loss: 0.007179, Train_acc: 1.000000 Epoch:2, train_step: 2577, loss: 0.007202, Train_acc: 1.000000 Epoch:2, train_step: 2578, loss: 0.012028, Train_acc: 1.000000 Epoch:2, train_step: 2579, loss: 0.011747, Train_acc: 1.000000 Epoch:2, train_step: 2580, loss: 0.066926, Train_acc: 0.984375 Epoch:2, train_step: 2581, loss: 0.006218, Train_acc: 1.000000 Epoch:2, train_step: 2582, loss: 0.008392, Train_acc: 1.000000 Epoch:2, train_step: 2583, loss: 0.113521, Train_acc: 0.984375 Epoch:2, train_step: 2584, loss: 0.011058, Train_acc: 1.000000 Epoch:2, train_step: 2585, loss: 0.005119, Train_acc: 1.000000 Epoch:2, train_step: 2586, loss: 0.053153, Train_acc: 0.968750 Epoch:2, train_step: 2587, loss: 0.066001, Train_acc: 0.968750 Epoch:2, train_step: 2588, loss: 0.015233, Train_acc: 1.000000 Epoch:2, train_step: 2589, loss: 0.012516, Train_acc: 1.000000 Epoch:2, train_step: 2590, loss: 0.041632, Train_acc: 0.984375 Epoch:2, train_step: 2591, loss: 0.134357, Train_acc: 0.968750 Epoch:2, train_step: 2592, loss: 0.026310, Train_acc: 1.000000 Epoch:2, train_step: 2593, loss: 0.090399, Train_acc: 0.984375 Epoch:2, train_step: 2594, loss: 0.082489, Train_acc: 0.968750 Epoch:2, train_step: 2595, loss: 0.041190, Train_acc: 0.984375 Epoch:2, train_step: 2596, loss: 0.007427, Train_acc: 1.000000 Epoch:2, train_step: 2597, loss: 0.042975, Train_acc: 0.984375 Epoch:2, train_step: 2598, loss: 0.035108, Train_acc: 0.984375 Epoch:2, train_step: 2599, loss: 0.015500, Train_acc: 1.000000 Epoch:2, train_step: 2600, loss: 0.016642, Train_acc: 1.000000 Epoch:2, train_step: 2601, loss: 0.014136, Train_acc: 0.984375 Epoch:2, train_step: 2602, loss: 0.004021, Train_acc: 1.000000 Epoch:2, train_step: 2603, loss: 0.004100, Train_acc: 1.000000 Epoch:2, train_step: 2604, loss: 0.021153, Train_acc: 0.984375 Epoch:2, train_step: 2605, loss: 0.034331, Train_acc: 0.984375 Epoch:2, train_step: 2606, loss: 0.019574, Train_acc: 0.984375 Epoch:2, train_step: 2607, loss: 0.101693, Train_acc: 0.984375 Epoch:2, train_step: 2608, loss: 0.008180, Train_acc: 1.000000 Epoch:2, train_step: 2609, loss: 0.019838, Train_acc: 1.000000 Epoch:2, train_step: 2610, loss: 0.007837, Train_acc: 1.000000 Epoch:2, train_step: 2611, loss: 0.017758, Train_acc: 0.984375 Epoch:2, train_step: 2612, loss: 0.016019, Train_acc: 1.000000 Epoch:2, train_step: 2613, loss: 0.057512, Train_acc: 0.984375 Epoch:2, train_step: 2614, loss: 0.031913, Train_acc: 0.984375 Epoch:2, train_step: 2615, loss: 0.044700, Train_acc: 0.984375 Epoch:2, train_step: 2616, loss: 0.029113, Train_acc: 1.000000 Epoch:2, train_step: 2617, loss: 0.039991, Train_acc: 0.968750 Epoch:2, train_step: 2618, loss: 0.100180, Train_acc: 0.984375 Epoch:2, train_step: 2619, loss: 0.026093, Train_acc: 0.984375 Epoch:2, train_step: 2620, loss: 0.109765, Train_acc: 0.953125 Epoch:2, train_step: 2621, loss: 0.030644, Train_acc: 0.984375 Epoch:2, train_step: 2622, loss: 0.004227, Train_acc: 1.000000 Epoch:2, train_step: 2623, loss: 0.020477, Train_acc: 1.000000 Epoch:2, train_step: 2624, loss: 0.015211, Train_acc: 1.000000 Epoch:2, train_step: 2625, loss: 0.016833, Train_acc: 1.000000 Epoch:2, train_step: 2626, loss: 0.067963, Train_acc: 0.968750 Epoch:2, train_step: 2627, loss: 0.007405, Train_acc: 1.000000 Epoch:2, train_step: 2628, loss: 0.013119, Train_acc: 1.000000 Epoch:2, train_step: 2629, loss: 0.011524, Train_acc: 1.000000 Epoch:2, train_step: 2630, loss: 0.054366, Train_acc: 0.984375 Epoch:2, train_step: 2631, loss: 0.007820, Train_acc: 1.000000 Epoch:2, train_step: 2632, loss: 0.027102, Train_acc: 0.984375 Epoch:2, train_step: 2633, loss: 0.010454, Train_acc: 1.000000 Epoch:2, train_step: 2634, loss: 0.022293, Train_acc: 0.984375 Epoch:2, train_step: 2635, loss: 0.020583, Train_acc: 1.000000 Epoch:2, train_step: 2636, loss: 0.002701, Train_acc: 1.000000 Epoch:2, train_step: 2637, loss: 0.008000, Train_acc: 1.000000 Epoch:2, train_step: 2638, loss: 0.016207, Train_acc: 0.984375 Epoch:2, train_step: 2639, loss: 0.010145, Train_acc: 1.000000 Epoch:2, train_step: 2640, loss: 0.076861, Train_acc: 0.984375 Epoch:2, train_step: 2641, loss: 0.095045, Train_acc: 0.984375 Epoch:2, train_step: 2642, loss: 0.017411, Train_acc: 0.984375 Epoch:2, train_step: 2643, loss: 0.135827, Train_acc: 0.968750 Epoch:2, train_step: 2644, loss: 0.005649, Train_acc: 1.000000 Epoch:2, train_step: 2645, loss: 0.005691, Train_acc: 1.000000 Epoch:2, train_step: 2646, loss: 0.035656, Train_acc: 0.984375 Epoch:2, train_step: 2647, loss: 0.125232, Train_acc: 0.953125 Epoch:2, train_step: 2648, loss: 0.070117, Train_acc: 0.968750 Epoch:2, train_step: 2649, loss: 0.013218, Train_acc: 1.000000 Epoch:2, train_step: 2650, loss: 0.034272, Train_acc: 1.000000 Epoch:2, train_step: 2651, loss: 0.005502, Train_acc: 1.000000 Epoch:2, train_step: 2652, loss: 0.029067, Train_acc: 1.000000 Epoch:2, train_step: 2653, loss: 0.023883, Train_acc: 0.984375 Epoch:2, train_step: 2654, loss: 0.051257, Train_acc: 0.968750 Epoch:2, train_step: 2655, loss: 0.004695, Train_acc: 1.000000 Epoch:2, train_step: 2656, loss: 0.007673, Train_acc: 1.000000 Epoch:2, train_step: 2657, loss: 0.022869, Train_acc: 0.984375 Epoch:2, train_step: 2658, loss: 0.004524, Train_acc: 1.000000 Epoch:2, train_step: 2659, loss: 0.050737, Train_acc: 0.984375 Epoch:2, train_step: 2660, loss: 0.004761, Train_acc: 1.000000 Epoch:2, train_step: 2661, loss: 0.049928, Train_acc: 0.968750 Epoch:2, train_step: 2662, loss: 0.025653, Train_acc: 1.000000 Epoch:2, train_step: 2663, loss: 0.015289, Train_acc: 1.000000 Epoch:2, train_step: 2664, loss: 0.012736, Train_acc: 1.000000 Epoch:2, train_step: 2665, loss: 0.036004, Train_acc: 0.984375 Epoch:2, train_step: 2666, loss: 0.000878, Train_acc: 1.000000 Epoch:2, train_step: 2667, loss: 0.023201, Train_acc: 1.000000 Epoch:2, train_step: 2668, loss: 0.002072, Train_acc: 1.000000 Epoch:2, train_step: 2669, loss: 0.002288, Train_acc: 1.000000 Epoch:2, train_step: 2670, loss: 0.022783, Train_acc: 1.000000 Epoch:2, train_step: 2671, loss: 0.051699, Train_acc: 0.968750 Epoch:2, train_step: 2672, loss: 0.011792, Train_acc: 1.000000 Epoch:2, train_step: 2673, loss: 0.002227, Train_acc: 1.000000 Epoch:2, train_step: 2674, loss: 0.008540, Train_acc: 1.000000 Epoch:2, train_step: 2675, loss: 0.051961, Train_acc: 0.984375 Epoch:2, train_step: 2676, loss: 0.037255, Train_acc: 0.968750 Epoch:2, train_step: 2677, loss: 0.003549, Train_acc: 1.000000 Epoch:2, train_step: 2678, loss: 0.008085, Train_acc: 1.000000 Epoch:2, train_step: 2679, loss: 0.011163, Train_acc: 1.000000 Epoch:2, train_step: 2680, loss: 0.016875, Train_acc: 0.984375 Epoch:2, train_step: 2681, loss: 0.006138, Train_acc: 1.000000 Epoch:2, train_step: 2682, loss: 0.013119, Train_acc: 1.000000 Epoch:2, train_step: 2683, loss: 0.033295, Train_acc: 0.984375 Epoch:2, train_step: 2684, loss: 0.004424, Train_acc: 1.000000 Epoch:2, train_step: 2685, loss: 0.001662, Train_acc: 1.000000 Epoch:2, train_step: 2686, loss: 0.137422, Train_acc: 0.984375 Epoch:2, train_step: 2687, loss: 0.014645, Train_acc: 1.000000 Epoch:2, train_step: 2688, loss: 0.007458, Train_acc: 1.000000 Epoch:2, train_step: 2689, loss: 0.026886, Train_acc: 1.000000 Epoch:2, train_step: 2690, loss: 0.025419, Train_acc: 0.984375 Epoch:2, train_step: 2691, loss: 0.006252, Train_acc: 1.000000 Epoch:2, train_step: 2692, loss: 0.015688, Train_acc: 1.000000 Epoch:2, train_step: 2693, loss: 0.012163, Train_acc: 1.000000 Epoch:2, train_step: 2694, loss: 0.016498, Train_acc: 0.984375 Epoch:2, train_step: 2695, loss: 0.046069, Train_acc: 0.984375 Epoch:2, train_step: 2696, loss: 0.003085, Train_acc: 1.000000 Epoch:2, train_step: 2697, loss: 0.004019, Train_acc: 1.000000 Epoch:2, train_step: 2698, loss: 0.008540, Train_acc: 1.000000 Epoch:2, train_step: 2699, loss: 0.016149, Train_acc: 1.000000 Epoch:2, train_step: 2700, loss: 0.056539, Train_acc: 0.968750 Epoch:2, train_step: 2701, loss: 0.033542, Train_acc: 0.968750 Epoch:2, train_step: 2702, loss: 0.286972, Train_acc: 0.937500 Epoch:2, train_step: 2703, loss: 0.008970, Train_acc: 1.000000 Epoch:2, train_step: 2704, loss: 0.004348, Train_acc: 1.000000 Epoch:2, train_step: 2705, loss: 0.004340, Train_acc: 1.000000 Epoch:2, train_step: 2706, loss: 0.008803, Train_acc: 1.000000 Epoch:2, train_step: 2707, loss: 0.001208, Train_acc: 1.000000 Epoch:2, train_step: 2708, loss: 0.011929, Train_acc: 0.984375 Epoch:2, train_step: 2709, loss: 0.076533, Train_acc: 0.984375 Epoch:2, train_step: 2710, loss: 0.023993, Train_acc: 1.000000 Epoch:2, train_step: 2711, loss: 0.028627, Train_acc: 0.984375 Epoch:2, train_step: 2712, loss: 0.005494, Train_acc: 1.000000 Epoch:2, train_step: 2713, loss: 0.084669, Train_acc: 0.953125 Epoch:2, train_step: 2714, loss: 0.006466, Train_acc: 1.000000 Epoch:2, train_step: 2715, loss: 0.038221, Train_acc: 0.984375 Epoch:2, train_step: 2716, loss: 0.020220, Train_acc: 1.000000 Epoch:2, train_step: 2717, loss: 0.008175, Train_acc: 1.000000 Epoch:2, train_step: 2718, loss: 0.030952, Train_acc: 0.984375 Epoch:2, train_step: 2719, loss: 0.053168, Train_acc: 0.968750 Epoch:2, train_step: 2720, loss: 0.012546, Train_acc: 1.000000 Epoch:2, train_step: 2721, loss: 0.021632, Train_acc: 0.984375 Epoch:2, train_step: 2722, loss: 0.021109, Train_acc: 0.984375 Epoch:2, train_step: 2723, loss: 0.064107, Train_acc: 0.984375 Epoch:2, train_step: 2724, loss: 0.018561, Train_acc: 0.984375 Epoch:2, train_step: 2725, loss: 0.026320, Train_acc: 0.984375 Epoch:2, train_step: 2726, loss: 0.017864, Train_acc: 0.984375 Epoch:2, train_step: 2727, loss: 0.017428, Train_acc: 1.000000 Epoch:2, train_step: 2728, loss: 0.012447, Train_acc: 0.984375 Epoch:2, train_step: 2729, loss: 0.013946, Train_acc: 1.000000 Epoch:2, train_step: 2730, loss: 0.008061, Train_acc: 1.000000 Epoch:2, train_step: 2731, loss: 0.047390, Train_acc: 0.984375 Epoch:2, train_step: 2732, loss: 0.069826, Train_acc: 0.984375 Epoch:2, train_step: 2733, loss: 0.004813, Train_acc: 1.000000 Epoch:2, train_step: 2734, loss: 0.003198, Train_acc: 1.000000 Epoch:2, train_step: 2735, loss: 0.011092, Train_acc: 1.000000 Epoch:2, train_step: 2736, loss: 0.001573, Train_acc: 1.000000 Epoch:2, train_step: 2737, loss: 0.002629, Train_acc: 1.000000 Epoch:2, train_step: 2738, loss: 0.027831, Train_acc: 0.984375 Epoch:2, train_step: 2739, loss: 0.041327, Train_acc: 0.984375 Epoch:2, train_step: 2740, loss: 0.086305, Train_acc: 0.968750 Epoch:2, train_step: 2741, loss: 0.032188, Train_acc: 1.000000 Epoch:2, train_step: 2742, loss: 0.018757, Train_acc: 1.000000 Epoch:2, train_step: 2743, loss: 0.071980, Train_acc: 0.968750 Epoch:2, train_step: 2744, loss: 0.003346, Train_acc: 1.000000 Epoch:2, train_step: 2745, loss: 0.063884, Train_acc: 0.968750 Epoch:2, train_step: 2746, loss: 0.018546, Train_acc: 0.984375 Epoch:2, train_step: 2747, loss: 0.010466, Train_acc: 1.000000 Epoch:2, train_step: 2748, loss: 0.014039, Train_acc: 1.000000 Epoch:2, train_step: 2749, loss: 0.026797, Train_acc: 0.984375 Epoch:2, train_step: 2750, loss: 0.043638, Train_acc: 0.984375 Epoch:2, train_step: 2751, loss: 0.024728, Train_acc: 0.984375 Epoch:2, train_step: 2752, loss: 0.069161, Train_acc: 0.984375 Epoch:2, train_step: 2753, loss: 0.049728, Train_acc: 0.984375 Epoch:2, train_step: 2754, loss: 0.023865, Train_acc: 1.000000 Epoch:2, train_step: 2755, loss: 0.035389, Train_acc: 0.984375 Epoch:2, train_step: 2756, loss: 0.056049, Train_acc: 0.984375 Epoch:2, train_step: 2757, loss: 0.092270, Train_acc: 0.968750 Epoch:2, train_step: 2758, loss: 0.001120, Train_acc: 1.000000 Epoch:2, train_step: 2759, loss: 0.022169, Train_acc: 0.984375 Epoch:2, train_step: 2760, loss: 0.010187, Train_acc: 1.000000 Epoch:2, train_step: 2761, loss: 0.010109, Train_acc: 1.000000 Epoch:2, train_step: 2762, loss: 0.069673, Train_acc: 0.984375 Epoch:2, train_step: 2763, loss: 0.021443, Train_acc: 1.000000 Epoch:2, train_step: 2764, loss: 0.005311, Train_acc: 1.000000 Epoch:2, train_step: 2765, loss: 0.005075, Train_acc: 1.000000 Epoch:2, train_step: 2766, loss: 0.009806, Train_acc: 1.000000 Epoch:2, train_step: 2767, loss: 0.000322, Train_acc: 1.000000 Epoch:2, train_step: 2768, loss: 0.001866, Train_acc: 1.000000 Epoch:2, train_step: 2769, loss: 0.018497, Train_acc: 1.000000 Epoch:2, train_step: 2770, loss: 0.010115, Train_acc: 1.000000 Epoch:2, train_step: 2771, loss: 0.005547, Train_acc: 1.000000 Epoch:2, train_step: 2772, loss: 0.003562, Train_acc: 1.000000 Epoch:2, train_step: 2773, loss: 0.022191, Train_acc: 1.000000 Epoch:2, train_step: 2774, loss: 0.005488, Train_acc: 1.000000 Epoch:2, train_step: 2775, loss: 0.030948, Train_acc: 1.000000 Epoch:2, train_step: 2776, loss: 0.005884, Train_acc: 1.000000 Epoch:2, train_step: 2777, loss: 0.109762, Train_acc: 0.984375 Epoch:2, train_step: 2778, loss: 0.054122, Train_acc: 0.953125 Epoch:2, train_step: 2779, loss: 0.014606, Train_acc: 1.000000 Epoch:2, train_step: 2780, loss: 0.028236, Train_acc: 0.984375 Epoch:2, train_step: 2781, loss: 0.013556, Train_acc: 0.984375 Epoch:2, train_step: 2782, loss: 0.097502, Train_acc: 0.984375 Epoch:2, train_step: 2783, loss: 0.001039, Train_acc: 1.000000 Epoch:2, train_step: 2784, loss: 0.006006, Train_acc: 1.000000 Epoch:2, train_step: 2785, loss: 0.001564, Train_acc: 1.000000 Epoch:2, train_step: 2786, loss: 0.004349, Train_acc: 1.000000 Epoch:2, train_step: 2787, loss: 0.008669, Train_acc: 1.000000 Epoch:2, train_step: 2788, loss: 0.007857, Train_acc: 1.000000 Epoch:2, train_step: 2789, loss: 0.007225, Train_acc: 1.000000 Epoch:2, train_step: 2790, loss: 0.001098, Train_acc: 1.000000 Epoch:2, train_step: 2791, loss: 0.014453, Train_acc: 1.000000 Epoch:2, train_step: 2792, loss: 0.000137, Train_acc: 1.000000 Epoch:2, train_step: 2793, loss: 0.012418, Train_acc: 1.000000 Epoch:2, train_step: 2794, loss: 0.016799, Train_acc: 0.984375 Epoch:2, train_step: 2795, loss: 0.002365, Train_acc: 1.000000 Epoch:2, train_step: 2796, loss: 0.000227, Train_acc: 1.000000 Epoch:2, train_step: 2797, loss: 0.001221, Train_acc: 1.000000 Epoch:2, train_step: 2798, loss: 0.001608, Train_acc: 1.000000 Epoch:2, train_step: 2799, loss: 0.000195, Train_acc: 1.000000 Epoch:2, train_step: 2800, loss: 0.000415, Train_acc: 1.000000 Epoch:2, train_step: 2801, loss: 0.014176, Train_acc: 1.000000 Epoch:2, train_step: 2802, loss: 0.020000, Train_acc: 0.984375 Epoch:2, train_step: 2803, loss: 0.002377, Train_acc: 1.000000 Epoch:2, train_step: 2804, loss: 0.009519, Train_acc: 1.000000 Epoch:2, train_step: 2805, loss: 0.000452, Train_acc: 1.000000 Epoch:2, train_step: 2806, loss: 0.001504, Train_acc: 1.000000 Epoch:2, train_step: 2807, loss: 0.073860, Train_acc: 0.968750 Epoch:2, train_step: 2808, loss: 0.177141, Train_acc: 0.968750 Epoch:2, train_step: 2809, loss: 0.002303, Train_acc: 1.000000 Epoch:2, train_step: 2810, loss: 0.000907, Train_acc: 1.000000 Epoch:2, train_step: 2811, loss: 0.187105, Train_acc: 0.984375 Epoch:2, avg_train_loss: 0.034751, avg_train_acc: 0.989511, Test_acc: 0.985477 Epoch:3, train_step: 2812, loss: 0.018478, Train_acc: 0.984375 Epoch:3, train_step: 2813, loss: 0.024846, Train_acc: 1.000000 Epoch:3, train_step: 2814, loss: 0.184328, Train_acc: 0.968750 Epoch:3, train_step: 2815, loss: 0.033348, Train_acc: 0.984375 Epoch:3, train_step: 2816, loss: 0.011308, Train_acc: 1.000000 Epoch:3, train_step: 2817, loss: 0.004363, Train_acc: 1.000000 Epoch:3, train_step: 2818, loss: 0.033815, Train_acc: 0.984375 Epoch:3, train_step: 2819, loss: 0.161287, Train_acc: 0.953125 Epoch:3, train_step: 2820, loss: 0.003903, Train_acc: 1.000000 Epoch:3, train_step: 2821, loss: 0.139119, Train_acc: 0.968750 Epoch:3, train_step: 2822, loss: 0.008131, Train_acc: 1.000000 Epoch:3, train_step: 2823, loss: 0.015766, Train_acc: 1.000000 Epoch:3, train_step: 2824, loss: 0.022582, Train_acc: 0.984375 Epoch:3, train_step: 2825, loss: 0.029572, Train_acc: 0.984375 Epoch:3, train_step: 2826, loss: 0.083495, Train_acc: 0.984375 Epoch:3, train_step: 2827, loss: 0.035984, Train_acc: 0.984375 Epoch:3, train_step: 2828, loss: 0.015625, Train_acc: 1.000000 Epoch:3, train_step: 2829, loss: 0.042761, Train_acc: 0.984375 Epoch:3, train_step: 2830, loss: 0.022046, Train_acc: 0.984375 Epoch:3, train_step: 2831, loss: 0.015674, Train_acc: 1.000000 Epoch:3, train_step: 2832, loss: 0.069076, Train_acc: 0.968750 Epoch:3, train_step: 2833, loss: 0.081501, Train_acc: 0.968750 Epoch:3, train_step: 2834, loss: 0.001563, Train_acc: 1.000000 Epoch:3, train_step: 2835, loss: 0.003347, Train_acc: 1.000000 Epoch:3, train_step: 2836, loss: 0.002182, Train_acc: 1.000000 Epoch:3, train_step: 2837, loss: 0.166720, Train_acc: 0.968750 Epoch:3, train_step: 2838, loss: 0.004326, Train_acc: 1.000000 Epoch:3, train_step: 2839, loss: 0.102479, Train_acc: 0.968750 Epoch:3, train_step: 2840, loss: 0.009722, Train_acc: 1.000000 Epoch:3, train_step: 2841, loss: 0.004085, Train_acc: 1.000000 Epoch:3, train_step: 2842, loss: 0.012796, Train_acc: 1.000000 Epoch:3, train_step: 2843, loss: 0.044372, Train_acc: 0.984375 Epoch:3, train_step: 2844, loss: 0.007292, Train_acc: 1.000000 Epoch:3, train_step: 2845, loss: 0.008401, Train_acc: 1.000000 Epoch:3, train_step: 2846, loss: 0.065598, Train_acc: 0.984375 Epoch:3, train_step: 2847, loss: 0.017590, Train_acc: 1.000000 Epoch:3, train_step: 2848, loss: 0.001287, Train_acc: 1.000000 Epoch:3, train_step: 2849, loss: 0.039398, Train_acc: 0.968750 Epoch:3, train_step: 2850, loss: 0.002469, Train_acc: 1.000000 Epoch:3, train_step: 2851, loss: 0.019431, Train_acc: 0.984375 Epoch:3, train_step: 2852, loss: 0.009353, Train_acc: 1.000000 Epoch:3, train_step: 2853, loss: 0.039959, Train_acc: 0.984375 Epoch:3, train_step: 2854, loss: 0.134177, Train_acc: 0.968750 Epoch:3, train_step: 2855, loss: 0.019985, Train_acc: 1.000000 Epoch:3, train_step: 2856, loss: 0.005892, Train_acc: 1.000000 Epoch:3, train_step: 2857, loss: 0.007810, Train_acc: 1.000000 Epoch:3, train_step: 2858, loss: 0.002313, Train_acc: 1.000000 Epoch:3, train_step: 2859, loss: 0.011195, Train_acc: 1.000000 Epoch:3, train_step: 2860, loss: 0.002003, Train_acc: 1.000000 Epoch:3, train_step: 2861, loss: 0.000619, Train_acc: 1.000000 Epoch:3, train_step: 2862, loss: 0.095354, Train_acc: 0.984375 Epoch:3, train_step: 2863, loss: 0.006953, Train_acc: 1.000000 Epoch:3, train_step: 2864, loss: 0.003236, Train_acc: 1.000000 Epoch:3, train_step: 2865, loss: 0.022052, Train_acc: 1.000000 Epoch:3, train_step: 2866, loss: 0.009364, Train_acc: 1.000000 Epoch:3, train_step: 2867, loss: 0.015427, Train_acc: 1.000000 Epoch:3, train_step: 2868, loss: 0.011596, Train_acc: 1.000000 Epoch:3, train_step: 2869, loss: 0.221677, Train_acc: 0.953125 Epoch:3, train_step: 2870, loss: 0.035883, Train_acc: 0.984375 Epoch:3, train_step: 2871, loss: 0.007574, Train_acc: 1.000000 Epoch:3, train_step: 2872, loss: 0.017079, Train_acc: 0.984375 Epoch:3, train_step: 2873, loss: 0.035072, Train_acc: 0.984375 Epoch:3, train_step: 2874, loss: 0.012018, Train_acc: 1.000000 Epoch:3, train_step: 2875, loss: 0.014400, Train_acc: 1.000000 Epoch:3, train_step: 2876, loss: 0.018167, Train_acc: 1.000000 Epoch:3, train_step: 2877, loss: 0.002819, Train_acc: 1.000000 Epoch:3, train_step: 2878, loss: 0.016021, Train_acc: 1.000000 Epoch:3, train_step: 2879, loss: 0.010202, Train_acc: 1.000000 Epoch:3, train_step: 2880, loss: 0.018895, Train_acc: 0.984375 Epoch:3, train_step: 2881, loss: 0.098812, Train_acc: 0.968750 Epoch:3, train_step: 2882, loss: 0.003493, Train_acc: 1.000000 Epoch:3, train_step: 2883, loss: 0.006514, Train_acc: 1.000000 Epoch:3, train_step: 2884, loss: 0.020370, Train_acc: 0.984375 Epoch:3, train_step: 2885, loss: 0.009642, Train_acc: 1.000000 Epoch:3, train_step: 2886, loss: 0.013280, Train_acc: 1.000000 Epoch:3, train_step: 2887, loss: 0.027275, Train_acc: 0.984375 Epoch:3, train_step: 2888, loss: 0.001996, Train_acc: 1.000000 Epoch:3, train_step: 2889, loss: 0.005509, Train_acc: 1.000000 Epoch:3, train_step: 2890, loss: 0.033209, Train_acc: 0.984375 Epoch:3, train_step: 2891, loss: 0.006740, Train_acc: 1.000000 Epoch:3, train_step: 2892, loss: 0.011388, Train_acc: 1.000000 Epoch:3, train_step: 2893, loss: 0.026206, Train_acc: 1.000000 Epoch:3, train_step: 2894, loss: 0.012467, Train_acc: 1.000000 Epoch:3, train_step: 2895, loss: 0.018371, Train_acc: 1.000000 Epoch:3, train_step: 2896, loss: 0.007832, Train_acc: 1.000000 Epoch:3, train_step: 2897, loss: 0.014931, Train_acc: 1.000000 Epoch:3, train_step: 2898, loss: 0.020492, Train_acc: 0.984375 Epoch:3, train_step: 2899, loss: 0.013735, Train_acc: 1.000000 Epoch:3, train_step: 2900, loss: 0.014492, Train_acc: 1.000000 Epoch:3, train_step: 2901, loss: 0.096533, Train_acc: 0.968750 Epoch:3, train_step: 2902, loss: 0.064216, Train_acc: 0.984375 Epoch:3, train_step: 2903, loss: 0.019109, Train_acc: 1.000000 Epoch:3, train_step: 2904, loss: 0.040814, Train_acc: 0.984375 Epoch:3, train_step: 2905, loss: 0.021987, Train_acc: 0.984375 Epoch:3, train_step: 2906, loss: 0.010553, Train_acc: 1.000000 Epoch:3, train_step: 2907, loss: 0.021950, Train_acc: 0.984375 Epoch:3, train_step: 2908, loss: 0.001581, Train_acc: 1.000000 Epoch:3, train_step: 2909, loss: 0.112620, Train_acc: 0.953125 Epoch:3, train_step: 2910, loss: 0.011887, Train_acc: 1.000000 Epoch:3, train_step: 2911, loss: 0.006214, Train_acc: 1.000000 Epoch:3, train_step: 2912, loss: 0.016298, Train_acc: 1.000000 Epoch:3, train_step: 2913, loss: 0.008139, Train_acc: 1.000000 Epoch:3, train_step: 2914, loss: 0.012698, Train_acc: 1.000000 Epoch:3, train_step: 2915, loss: 0.002561, Train_acc: 1.000000 Epoch:3, train_step: 2916, loss: 0.055852, Train_acc: 0.968750 Epoch:3, train_step: 2917, loss: 0.001253, Train_acc: 1.000000 Epoch:3, train_step: 2918, loss: 0.042977, Train_acc: 0.984375 Epoch:3, train_step: 2919, loss: 0.108379, Train_acc: 0.968750 Epoch:3, train_step: 2920, loss: 0.013535, Train_acc: 1.000000 Epoch:3, train_step: 2921, loss: 0.051259, Train_acc: 0.984375 Epoch:3, train_step: 2922, loss: 0.091883, Train_acc: 0.984375 Epoch:3, train_step: 2923, loss: 0.004381, Train_acc: 1.000000 Epoch:3, train_step: 2924, loss: 0.025768, Train_acc: 1.000000 Epoch:3, train_step: 2925, loss: 0.282928, Train_acc: 0.953125 Epoch:3, train_step: 2926, loss: 0.027051, Train_acc: 0.984375 Epoch:3, train_step: 2927, loss: 0.007485, Train_acc: 1.000000 Epoch:3, train_step: 2928, loss: 0.007569, Train_acc: 1.000000 Epoch:3, train_step: 2929, loss: 0.010365, Train_acc: 1.000000 Epoch:3, train_step: 2930, loss: 0.111325, Train_acc: 0.968750 Epoch:3, train_step: 2931, loss: 0.052265, Train_acc: 0.984375 Epoch:3, train_step: 2932, loss: 0.019962, Train_acc: 1.000000 Epoch:3, train_step: 2933, loss: 0.016847, Train_acc: 1.000000 Epoch:3, train_step: 2934, loss: 0.055196, Train_acc: 0.968750 Epoch:3, train_step: 2935, loss: 0.007526, Train_acc: 1.000000 Epoch:3, train_step: 2936, loss: 0.054061, Train_acc: 0.968750 Epoch:3, train_step: 2937, loss: 0.026619, Train_acc: 0.984375 Epoch:3, train_step: 2938, loss: 0.063170, Train_acc: 0.968750 Epoch:3, train_step: 2939, loss: 0.002014, Train_acc: 1.000000 Epoch:3, train_step: 2940, loss: 0.032270, Train_acc: 0.984375 Epoch:3, train_step: 2941, loss: 0.010334, Train_acc: 1.000000 Epoch:3, train_step: 2942, loss: 0.009514, Train_acc: 1.000000 Epoch:3, train_step: 2943, loss: 0.005567, Train_acc: 1.000000 Epoch:3, train_step: 2944, loss: 0.007321, Train_acc: 1.000000 Epoch:3, train_step: 2945, loss: 0.004127, Train_acc: 1.000000 Epoch:3, train_step: 2946, loss: 0.035106, Train_acc: 0.984375 Epoch:3, train_step: 2947, loss: 0.020013, Train_acc: 1.000000 Epoch:3, train_step: 2948, loss: 0.031143, Train_acc: 0.968750 Epoch:3, train_step: 2949, loss: 0.007757, Train_acc: 1.000000 Epoch:3, train_step: 2950, loss: 0.061492, Train_acc: 0.968750 Epoch:3, train_step: 2951, loss: 0.034325, Train_acc: 0.984375 Epoch:3, train_step: 2952, loss: 0.005615, Train_acc: 1.000000 Epoch:3, train_step: 2953, loss: 0.009089, Train_acc: 1.000000 Epoch:3, train_step: 2954, loss: 0.020094, Train_acc: 1.000000 Epoch:3, train_step: 2955, loss: 0.004228, Train_acc: 1.000000 Epoch:3, train_step: 2956, loss: 0.026380, Train_acc: 0.984375 Epoch:3, train_step: 2957, loss: 0.007315, Train_acc: 1.000000 Epoch:3, train_step: 2958, loss: 0.038816, Train_acc: 0.984375 Epoch:3, train_step: 2959, loss: 0.052798, Train_acc: 0.984375 Epoch:3, train_step: 2960, loss: 0.017936, Train_acc: 0.984375 Epoch:3, train_step: 2961, loss: 0.026307, Train_acc: 0.984375 Epoch:3, train_step: 2962, loss: 0.009688, Train_acc: 1.000000 Epoch:3, train_step: 2963, loss: 0.012990, Train_acc: 1.000000 Epoch:3, train_step: 2964, loss: 0.079947, Train_acc: 0.984375 Epoch:3, train_step: 2965, loss: 0.000637, Train_acc: 1.000000 Epoch:3, train_step: 2966, loss: 0.011974, Train_acc: 1.000000 Epoch:3, train_step: 2967, loss: 0.011543, Train_acc: 1.000000 Epoch:3, train_step: 2968, loss: 0.003959, Train_acc: 1.000000 Epoch:3, train_step: 2969, loss: 0.034370, Train_acc: 0.984375 Epoch:3, train_step: 2970, loss: 0.016170, Train_acc: 1.000000 Epoch:3, train_step: 2971, loss: 0.048070, Train_acc: 0.984375 Epoch:3, train_step: 2972, loss: 0.024483, Train_acc: 1.000000 Epoch:3, train_step: 2973, loss: 0.013590, Train_acc: 0.984375 Epoch:3, train_step: 2974, loss: 0.020742, Train_acc: 0.984375 Epoch:3, train_step: 2975, loss: 0.002284, Train_acc: 1.000000 Epoch:3, train_step: 2976, loss: 0.003862, Train_acc: 1.000000 Epoch:3, train_step: 2977, loss: 0.001290, Train_acc: 1.000000 Epoch:3, train_step: 2978, loss: 0.009031, Train_acc: 1.000000 Epoch:3, train_step: 2979, loss: 0.003311, Train_acc: 1.000000 Epoch:3, train_step: 2980, loss: 0.049019, Train_acc: 0.984375 Epoch:3, train_step: 2981, loss: 0.008466, Train_acc: 1.000000 Epoch:3, train_step: 2982, loss: 0.002528, Train_acc: 1.000000 Epoch:3, train_step: 2983, loss: 0.124536, Train_acc: 0.984375 Epoch:3, train_step: 2984, loss: 0.047097, Train_acc: 0.984375 Epoch:3, train_step: 2985, loss: 0.001771, Train_acc: 1.000000 Epoch:3, train_step: 2986, loss: 0.002878, Train_acc: 1.000000 Epoch:3, train_step: 2987, loss: 0.104581, Train_acc: 0.984375 Epoch:3, train_step: 2988, loss: 0.010045, Train_acc: 1.000000 Epoch:3, train_step: 2989, loss: 0.041965, Train_acc: 0.968750 Epoch:3, train_step: 2990, loss: 0.011937, Train_acc: 1.000000 Epoch:3, train_step: 2991, loss: 0.002281, Train_acc: 1.000000 Epoch:3, train_step: 2992, loss: 0.032480, Train_acc: 0.984375 Epoch:3, train_step: 2993, loss: 0.013275, Train_acc: 1.000000 Epoch:3, train_step: 2994, loss: 0.005213, Train_acc: 1.000000 Epoch:3, train_step: 2995, loss: 0.006203, Train_acc: 1.000000 Epoch:3, train_step: 2996, loss: 0.029444, Train_acc: 1.000000 Epoch:3, train_step: 2997, loss: 0.027548, Train_acc: 0.984375 Epoch:3, train_step: 2998, loss: 0.026309, Train_acc: 0.984375 Epoch:3, train_step: 2999, loss: 0.007133, Train_acc: 1.000000 Epoch:3, train_step: 3000, loss: 0.018180, Train_acc: 0.984375 Epoch:3, train_step: 3001, loss: 0.001969, Train_acc: 1.000000 Epoch:3, train_step: 3002, loss: 0.008014, Train_acc: 1.000000 Epoch:3, train_step: 3003, loss: 0.007898, Train_acc: 1.000000 Epoch:3, train_step: 3004, loss: 0.011543, Train_acc: 1.000000 Epoch:3, train_step: 3005, loss: 0.008032, Train_acc: 1.000000 Epoch:3, train_step: 3006, loss: 0.004326, Train_acc: 1.000000 Epoch:3, train_step: 3007, loss: 0.000618, Train_acc: 1.000000 Epoch:3, train_step: 3008, loss: 0.084039, Train_acc: 0.984375 Epoch:3, train_step: 3009, loss: 0.049622, Train_acc: 0.984375 Epoch:3, train_step: 3010, loss: 0.001637, Train_acc: 1.000000 Epoch:3, train_step: 3011, loss: 0.007230, Train_acc: 1.000000 Epoch:3, train_step: 3012, loss: 0.034168, Train_acc: 0.984375 Epoch:3, train_step: 3013, loss: 0.031800, Train_acc: 0.984375 Epoch:3, train_step: 3014, loss: 0.057846, Train_acc: 0.984375 Epoch:3, train_step: 3015, loss: 0.020843, Train_acc: 1.000000 Epoch:3, train_step: 3016, loss: 0.008282, Train_acc: 1.000000 Epoch:3, train_step: 3017, loss: 0.005373, Train_acc: 1.000000 Epoch:3, train_step: 3018, loss: 0.004988, Train_acc: 1.000000 Epoch:3, train_step: 3019, loss: 0.001971, Train_acc: 1.000000 Epoch:3, train_step: 3020, loss: 0.010427, Train_acc: 1.000000 Epoch:3, train_step: 3021, loss: 0.020780, Train_acc: 0.984375 Epoch:3, train_step: 3022, loss: 0.004482, Train_acc: 1.000000 Epoch:3, train_step: 3023, loss: 0.004778, Train_acc: 1.000000 Epoch:3, train_step: 3024, loss: 0.002991, Train_acc: 1.000000 Epoch:3, train_step: 3025, loss: 0.009041, Train_acc: 1.000000 Epoch:3, train_step: 3026, loss: 0.015075, Train_acc: 1.000000 Epoch:3, train_step: 3027, loss: 0.001324, Train_acc: 1.000000 Epoch:3, train_step: 3028, loss: 0.068427, Train_acc: 0.984375 Epoch:3, train_step: 3029, loss: 0.005625, Train_acc: 1.000000 Epoch:3, train_step: 3030, loss: 0.037265, Train_acc: 0.984375 Epoch:3, train_step: 3031, loss: 0.028445, Train_acc: 0.984375 Epoch:3, train_step: 3032, loss: 0.027497, Train_acc: 0.984375 Epoch:3, train_step: 3033, loss: 0.004627, Train_acc: 1.000000 Epoch:3, train_step: 3034, loss: 0.023520, Train_acc: 0.984375 Epoch:3, train_step: 3035, loss: 0.015789, Train_acc: 1.000000 Epoch:3, train_step: 3036, loss: 0.005503, Train_acc: 1.000000 Epoch:3, train_step: 3037, loss: 0.010095, Train_acc: 1.000000 Epoch:3, train_step: 3038, loss: 0.005290, Train_acc: 1.000000 Epoch:3, train_step: 3039, loss: 0.112506, Train_acc: 0.968750 Epoch:3, train_step: 3040, loss: 0.002458, Train_acc: 1.000000 Epoch:3, train_step: 3041, loss: 0.032790, Train_acc: 0.984375 Epoch:3, train_step: 3042, loss: 0.009140, Train_acc: 1.000000 Epoch:3, train_step: 3043, loss: 0.015971, Train_acc: 1.000000 Epoch:3, train_step: 3044, loss: 0.001347, Train_acc: 1.000000 Epoch:3, train_step: 3045, loss: 0.004432, Train_acc: 1.000000 Epoch:3, train_step: 3046, loss: 0.000510, Train_acc: 1.000000 Epoch:3, train_step: 3047, loss: 0.028835, Train_acc: 0.984375 Epoch:3, train_step: 3048, loss: 0.009946, Train_acc: 1.000000 Epoch:3, train_step: 3049, loss: 0.006837, Train_acc: 1.000000 Epoch:3, train_step: 3050, loss: 0.001293, Train_acc: 1.000000 Epoch:3, train_step: 3051, loss: 0.041910, Train_acc: 0.984375 Epoch:3, train_step: 3052, loss: 0.001887, Train_acc: 1.000000 Epoch:3, train_step: 3053, loss: 0.008362, Train_acc: 1.000000 Epoch:3, train_step: 3054, loss: 0.001713, Train_acc: 1.000000 Epoch:3, train_step: 3055, loss: 0.002429, Train_acc: 1.000000 Epoch:3, train_step: 3056, loss: 0.006151, Train_acc: 1.000000 Epoch:3, train_step: 3057, loss: 0.016410, Train_acc: 1.000000 Epoch:3, train_step: 3058, loss: 0.049296, Train_acc: 0.968750 Epoch:3, train_step: 3059, loss: 0.002710, Train_acc: 1.000000 Epoch:3, train_step: 3060, loss: 0.006564, Train_acc: 1.000000 Epoch:3, train_step: 3061, loss: 0.049028, Train_acc: 0.984375 Epoch:3, train_step: 3062, loss: 0.006320, Train_acc: 1.000000 Epoch:3, train_step: 3063, loss: 0.027293, Train_acc: 0.984375 Epoch:3, train_step: 3064, loss: 0.020407, Train_acc: 1.000000 Epoch:3, train_step: 3065, loss: 0.006340, Train_acc: 1.000000 Epoch:3, train_step: 3066, loss: 0.004099, Train_acc: 1.000000 Epoch:3, train_step: 3067, loss: 0.001204, Train_acc: 1.000000 Epoch:3, train_step: 3068, loss: 0.012530, Train_acc: 1.000000 Epoch:3, train_step: 3069, loss: 0.003165, Train_acc: 1.000000 Epoch:3, train_step: 3070, loss: 0.015041, Train_acc: 0.984375 Epoch:3, train_step: 3071, loss: 0.002496, Train_acc: 1.000000 Epoch:3, train_step: 3072, loss: 0.095336, Train_acc: 0.968750 Epoch:3, train_step: 3073, loss: 0.038052, Train_acc: 0.984375 Epoch:3, train_step: 3074, loss: 0.002501, Train_acc: 1.000000 Epoch:3, train_step: 3075, loss: 0.011402, Train_acc: 1.000000 Epoch:3, train_step: 3076, loss: 0.005944, Train_acc: 1.000000 Epoch:3, train_step: 3077, loss: 0.012991, Train_acc: 1.000000 Epoch:3, train_step: 3078, loss: 0.006831, Train_acc: 1.000000 Epoch:3, train_step: 3079, loss: 0.006060, Train_acc: 1.000000 Epoch:3, train_step: 3080, loss: 0.046021, Train_acc: 0.968750 Epoch:3, train_step: 3081, loss: 0.025801, Train_acc: 0.984375 Epoch:3, train_step: 3082, loss: 0.000862, Train_acc: 1.000000 Epoch:3, train_step: 3083, loss: 0.003834, Train_acc: 1.000000 Epoch:3, train_step: 3084, loss: 0.004718, Train_acc: 1.000000 Epoch:3, train_step: 3085, loss: 0.013360, Train_acc: 1.000000 Epoch:3, train_step: 3086, loss: 0.085367, Train_acc: 0.984375 Epoch:3, train_step: 3087, loss: 0.002320, Train_acc: 1.000000 Epoch:3, train_step: 3088, loss: 0.010101, Train_acc: 1.000000 Epoch:3, train_step: 3089, loss: 0.024311, Train_acc: 0.984375 Epoch:3, train_step: 3090, loss: 0.042244, Train_acc: 0.968750 Epoch:3, train_step: 3091, loss: 0.003700, Train_acc: 1.000000 Epoch:3, train_step: 3092, loss: 0.009836, Train_acc: 1.000000 Epoch:3, train_step: 3093, loss: 0.003232, Train_acc: 1.000000 Epoch:3, train_step: 3094, loss: 0.002916, Train_acc: 1.000000 Epoch:3, train_step: 3095, loss: 0.020427, Train_acc: 1.000000 Epoch:3, train_step: 3096, loss: 0.014740, Train_acc: 1.000000 Epoch:3, train_step: 3097, loss: 0.008216, Train_acc: 1.000000 Epoch:3, train_step: 3098, loss: 0.075599, Train_acc: 0.953125 Epoch:3, train_step: 3099, loss: 0.060929, Train_acc: 0.968750 Epoch:3, train_step: 3100, loss: 0.002338, Train_acc: 1.000000 Epoch:3, train_step: 3101, loss: 0.011216, Train_acc: 1.000000 Epoch:3, train_step: 3102, loss: 0.003126, Train_acc: 1.000000 Epoch:3, train_step: 3103, loss: 0.003420, Train_acc: 1.000000 Epoch:3, train_step: 3104, loss: 0.030262, Train_acc: 0.984375 Epoch:3, train_step: 3105, loss: 0.008487, Train_acc: 1.000000 Epoch:3, train_step: 3106, loss: 0.024013, Train_acc: 0.984375 Epoch:3, train_step: 3107, loss: 0.002633, Train_acc: 1.000000 Epoch:3, train_step: 3108, loss: 0.002237, Train_acc: 1.000000 Epoch:3, train_step: 3109, loss: 0.014193, Train_acc: 1.000000 Epoch:3, train_step: 3110, loss: 0.009941, Train_acc: 1.000000 Epoch:3, train_step: 3111, loss: 0.021753, Train_acc: 0.984375 Epoch:3, train_step: 3112, loss: 0.018145, Train_acc: 1.000000 Epoch:3, train_step: 3113, loss: 0.008429, Train_acc: 1.000000 Epoch:3, train_step: 3114, loss: 0.021063, Train_acc: 0.984375 Epoch:3, train_step: 3115, loss: 0.002343, Train_acc: 1.000000 Epoch:3, train_step: 3116, loss: 0.022327, Train_acc: 1.000000 Epoch:3, train_step: 3117, loss: 0.028876, Train_acc: 0.984375 Epoch:3, train_step: 3118, loss: 0.014098, Train_acc: 1.000000 Epoch:3, train_step: 3119, loss: 0.013252, Train_acc: 0.984375 Epoch:3, train_step: 3120, loss: 0.001395, Train_acc: 1.000000 Epoch:3, train_step: 3121, loss: 0.010763, Train_acc: 1.000000 Epoch:3, train_step: 3122, loss: 0.026723, Train_acc: 0.984375 Epoch:3, train_step: 3123, loss: 0.009124, Train_acc: 1.000000 Epoch:3, train_step: 3124, loss: 0.009864, Train_acc: 1.000000 Epoch:3, train_step: 3125, loss: 0.034701, Train_acc: 0.984375 Epoch:3, train_step: 3126, loss: 0.008945, Train_acc: 1.000000 Epoch:3, train_step: 3127, loss: 0.012171, Train_acc: 1.000000 Epoch:3, train_step: 3128, loss: 0.016668, Train_acc: 1.000000 Epoch:3, train_step: 3129, loss: 0.004031, Train_acc: 1.000000 Epoch:3, train_step: 3130, loss: 0.002372, Train_acc: 1.000000 Epoch:3, train_step: 3131, loss: 0.004939, Train_acc: 1.000000 Epoch:3, train_step: 3132, loss: 0.004352, Train_acc: 1.000000 Epoch:3, train_step: 3133, loss: 0.016207, Train_acc: 0.984375 Epoch:3, train_step: 3134, loss: 0.015168, Train_acc: 1.000000 Epoch:3, train_step: 3135, loss: 0.007522, Train_acc: 1.000000 Epoch:3, train_step: 3136, loss: 0.073112, Train_acc: 0.968750 Epoch:3, train_step: 3137, loss: 0.012417, Train_acc: 1.000000 Epoch:3, train_step: 3138, loss: 0.040682, Train_acc: 0.984375 Epoch:3, train_step: 3139, loss: 0.005245, Train_acc: 1.000000 Epoch:3, train_step: 3140, loss: 0.003047, Train_acc: 1.000000 Epoch:3, train_step: 3141, loss: 0.000454, Train_acc: 1.000000 Epoch:3, train_step: 3142, loss: 0.038446, Train_acc: 0.984375 Epoch:3, train_step: 3143, loss: 0.001696, Train_acc: 1.000000 Epoch:3, train_step: 3144, loss: 0.008592, Train_acc: 1.000000 Epoch:3, train_step: 3145, loss: 0.022845, Train_acc: 0.984375 Epoch:3, train_step: 3146, loss: 0.004903, Train_acc: 1.000000 Epoch:3, train_step: 3147, loss: 0.012252, Train_acc: 1.000000 Epoch:3, train_step: 3148, loss: 0.002569, Train_acc: 1.000000 Epoch:3, train_step: 3149, loss: 0.002531, Train_acc: 1.000000 Epoch:3, train_step: 3150, loss: 0.019790, Train_acc: 0.984375 Epoch:3, train_step: 3151, loss: 0.008604, Train_acc: 1.000000 Epoch:3, train_step: 3152, loss: 0.010235, Train_acc: 1.000000 Epoch:3, train_step: 3153, loss: 0.004914, Train_acc: 1.000000 Epoch:3, train_step: 3154, loss: 0.035766, Train_acc: 0.984375 Epoch:3, train_step: 3155, loss: 0.014160, Train_acc: 1.000000 Epoch:3, train_step: 3156, loss: 0.005236, Train_acc: 1.000000 Epoch:3, train_step: 3157, loss: 0.003982, Train_acc: 1.000000 Epoch:3, train_step: 3158, loss: 0.010511, Train_acc: 1.000000 Epoch:3, train_step: 3159, loss: 0.009095, Train_acc: 1.000000 Epoch:3, train_step: 3160, loss: 0.006329, Train_acc: 1.000000 Epoch:3, train_step: 3161, loss: 0.001233, Train_acc: 1.000000 Epoch:3, train_step: 3162, loss: 0.018379, Train_acc: 1.000000 Epoch:3, train_step: 3163, loss: 0.005823, Train_acc: 1.000000 Epoch:3, train_step: 3164, loss: 0.045262, Train_acc: 0.984375 Epoch:3, train_step: 3165, loss: 0.027805, Train_acc: 1.000000 Epoch:3, train_step: 3166, loss: 0.008086, Train_acc: 1.000000 Epoch:3, train_step: 3167, loss: 0.024198, Train_acc: 0.984375 Epoch:3, train_step: 3168, loss: 0.008010, Train_acc: 1.000000 Epoch:3, train_step: 3169, loss: 0.004328, Train_acc: 1.000000 Epoch:3, train_step: 3170, loss: 0.000168, Train_acc: 1.000000 Epoch:3, train_step: 3171, loss: 0.004040, Train_acc: 1.000000 Epoch:3, train_step: 3172, loss: 0.016830, Train_acc: 0.984375 Epoch:3, train_step: 3173, loss: 0.016034, Train_acc: 0.984375 Epoch:3, train_step: 3174, loss: 0.008609, Train_acc: 1.000000 Epoch:3, train_step: 3175, loss: 0.001297, Train_acc: 1.000000 Epoch:3, train_step: 3176, loss: 0.001196, Train_acc: 1.000000 Epoch:3, train_step: 3177, loss: 0.007000, Train_acc: 1.000000 Epoch:3, train_step: 3178, loss: 0.003701, Train_acc: 1.000000 Epoch:3, train_step: 3179, loss: 0.009889, Train_acc: 1.000000 Epoch:3, train_step: 3180, loss: 0.077609, Train_acc: 0.984375 Epoch:3, train_step: 3181, loss: 0.002039, Train_acc: 1.000000 Epoch:3, train_step: 3182, loss: 0.015582, Train_acc: 1.000000 Epoch:3, train_step: 3183, loss: 0.013926, Train_acc: 0.984375 Epoch:3, train_step: 3184, loss: 0.076170, Train_acc: 0.984375 Epoch:3, train_step: 3185, loss: 0.118297, Train_acc: 0.984375 Epoch:3, train_step: 3186, loss: 0.020141, Train_acc: 0.984375 Epoch:3, train_step: 3187, loss: 0.012317, Train_acc: 1.000000 Epoch:3, train_step: 3188, loss: 0.016707, Train_acc: 1.000000 Epoch:3, train_step: 3189, loss: 0.001715, Train_acc: 1.000000 Epoch:3, train_step: 3190, loss: 0.014383, Train_acc: 1.000000 Epoch:3, train_step: 3191, loss: 0.005935, Train_acc: 1.000000 Epoch:3, train_step: 3192, loss: 0.000508, Train_acc: 1.000000 Epoch:3, train_step: 3193, loss: 0.001822, Train_acc: 1.000000 Epoch:3, train_step: 3194, loss: 0.002302, Train_acc: 1.000000 Epoch:3, train_step: 3195, loss: 0.017266, Train_acc: 1.000000 Epoch:3, train_step: 3196, loss: 0.016066, Train_acc: 1.000000 Epoch:3, train_step: 3197, loss: 0.012992, Train_acc: 1.000000 Epoch:3, train_step: 3198, loss: 0.004591, Train_acc: 1.000000 Epoch:3, train_step: 3199, loss: 0.034114, Train_acc: 0.984375 Epoch:3, train_step: 3200, loss: 0.002971, Train_acc: 1.000000 Epoch:3, train_step: 3201, loss: 0.012830, Train_acc: 1.000000 Epoch:3, train_step: 3202, loss: 0.001804, Train_acc: 1.000000 Epoch:3, train_step: 3203, loss: 0.002618, Train_acc: 1.000000 Epoch:3, train_step: 3204, loss: 0.014085, Train_acc: 0.984375 Epoch:3, train_step: 3205, loss: 0.043314, Train_acc: 0.984375 Epoch:3, train_step: 3206, loss: 0.019815, Train_acc: 0.984375 Epoch:3, train_step: 3207, loss: 0.002929, Train_acc: 1.000000 Epoch:3, train_step: 3208, loss: 0.000366, Train_acc: 1.000000 Epoch:3, train_step: 3209, loss: 0.000609, Train_acc: 1.000000 Epoch:3, train_step: 3210, loss: 0.012664, Train_acc: 1.000000 Epoch:3, train_step: 3211, loss: 0.033365, Train_acc: 0.984375 Epoch:3, train_step: 3212, loss: 0.003526, Train_acc: 1.000000 Epoch:3, train_step: 3213, loss: 0.048050, Train_acc: 0.984375 Epoch:3, train_step: 3214, loss: 0.005211, Train_acc: 1.000000 Epoch:3, train_step: 3215, loss: 0.011721, Train_acc: 1.000000 Epoch:3, train_step: 3216, loss: 0.010464, Train_acc: 1.000000 Epoch:3, train_step: 3217, loss: 0.013586, Train_acc: 1.000000 Epoch:3, train_step: 3218, loss: 0.058194, Train_acc: 0.984375 Epoch:3, train_step: 3219, loss: 0.012000, Train_acc: 1.000000 Epoch:3, train_step: 3220, loss: 0.002371, Train_acc: 1.000000 Epoch:3, train_step: 3221, loss: 0.035544, Train_acc: 0.984375 Epoch:3, train_step: 3222, loss: 0.008748, Train_acc: 1.000000 Epoch:3, train_step: 3223, loss: 0.017336, Train_acc: 0.984375 Epoch:3, train_step: 3224, loss: 0.009317, Train_acc: 1.000000 Epoch:3, train_step: 3225, loss: 0.070194, Train_acc: 0.968750 Epoch:3, train_step: 3226, loss: 0.070702, Train_acc: 0.984375 Epoch:3, train_step: 3227, loss: 0.108521, Train_acc: 0.984375 Epoch:3, train_step: 3228, loss: 0.125442, Train_acc: 0.968750 Epoch:3, train_step: 3229, loss: 0.059034, Train_acc: 0.968750 Epoch:3, train_step: 3230, loss: 0.017467, Train_acc: 0.984375 Epoch:3, train_step: 3231, loss: 0.039439, Train_acc: 0.984375 Epoch:3, train_step: 3232, loss: 0.104916, Train_acc: 0.984375 Epoch:3, train_step: 3233, loss: 0.007166, Train_acc: 1.000000 Epoch:3, train_step: 3234, loss: 0.003001, Train_acc: 1.000000 Epoch:3, train_step: 3235, loss: 0.014046, Train_acc: 1.000000 Epoch:3, train_step: 3236, loss: 0.008562, Train_acc: 1.000000 Epoch:3, train_step: 3237, loss: 0.039921, Train_acc: 0.984375 Epoch:3, train_step: 3238, loss: 0.008987, Train_acc: 1.000000 Epoch:3, train_step: 3239, loss: 0.002509, Train_acc: 1.000000 Epoch:3, train_step: 3240, loss: 0.003182, Train_acc: 1.000000 Epoch:3, train_step: 3241, loss: 0.037030, Train_acc: 0.968750 Epoch:3, train_step: 3242, loss: 0.004329, Train_acc: 1.000000 Epoch:3, train_step: 3243, loss: 0.037840, Train_acc: 0.984375 Epoch:3, train_step: 3244, loss: 0.029062, Train_acc: 0.984375 Epoch:3, train_step: 3245, loss: 0.007384, Train_acc: 1.000000 Epoch:3, train_step: 3246, loss: 0.009938, Train_acc: 1.000000 Epoch:3, train_step: 3247, loss: 0.073393, Train_acc: 0.984375 Epoch:3, train_step: 3248, loss: 0.001936, Train_acc: 1.000000 Epoch:3, train_step: 3249, loss: 0.093093, Train_acc: 0.984375 Epoch:3, train_step: 3250, loss: 0.000401, Train_acc: 1.000000 Epoch:3, train_step: 3251, loss: 0.005836, Train_acc: 1.000000 Epoch:3, train_step: 3252, loss: 0.003756, Train_acc: 1.000000 Epoch:3, train_step: 3253, loss: 0.028278, Train_acc: 0.984375 Epoch:3, train_step: 3254, loss: 0.006267, Train_acc: 1.000000 Epoch:3, train_step: 3255, loss: 0.026537, Train_acc: 0.984375 Epoch:3, train_step: 3256, loss: 0.004161, Train_acc: 1.000000 Epoch:3, train_step: 3257, loss: 0.015188, Train_acc: 0.984375 Epoch:3, train_step: 3258, loss: 0.003228, Train_acc: 1.000000 Epoch:3, train_step: 3259, loss: 0.108267, Train_acc: 0.953125 Epoch:3, train_step: 3260, loss: 0.104589, Train_acc: 0.984375 Epoch:3, train_step: 3261, loss: 0.000624, Train_acc: 1.000000 Epoch:3, train_step: 3262, loss: 0.005215, Train_acc: 1.000000 Epoch:3, train_step: 3263, loss: 0.001989, Train_acc: 1.000000 Epoch:3, train_step: 3264, loss: 0.007542, Train_acc: 1.000000 Epoch:3, train_step: 3265, loss: 0.027547, Train_acc: 0.984375 Epoch:3, train_step: 3266, loss: 0.002143, Train_acc: 1.000000 Epoch:3, train_step: 3267, loss: 0.040396, Train_acc: 1.000000 Epoch:3, train_step: 3268, loss: 0.021934, Train_acc: 0.984375 Epoch:3, train_step: 3269, loss: 0.010332, Train_acc: 1.000000 Epoch:3, train_step: 3270, loss: 0.006500, Train_acc: 1.000000 Epoch:3, train_step: 3271, loss: 0.002184, Train_acc: 1.000000 Epoch:3, train_step: 3272, loss: 0.017262, Train_acc: 0.984375 Epoch:3, train_step: 3273, loss: 0.003335, Train_acc: 1.000000 Epoch:3, train_step: 3274, loss: 0.010841, Train_acc: 1.000000 Epoch:3, train_step: 3275, loss: 0.001778, Train_acc: 1.000000 Epoch:3, train_step: 3276, loss: 0.009811, Train_acc: 1.000000 Epoch:3, train_step: 3277, loss: 0.013526, Train_acc: 1.000000 Epoch:3, train_step: 3278, loss: 0.009470, Train_acc: 1.000000 Epoch:3, train_step: 3279, loss: 0.012974, Train_acc: 1.000000 Epoch:3, train_step: 3280, loss: 0.008779, Train_acc: 1.000000 Epoch:3, train_step: 3281, loss: 0.019399, Train_acc: 1.000000 Epoch:3, train_step: 3282, loss: 0.007186, Train_acc: 1.000000 Epoch:3, train_step: 3283, loss: 0.026016, Train_acc: 0.984375 Epoch:3, train_step: 3284, loss: 0.053612, Train_acc: 0.984375 Epoch:3, train_step: 3285, loss: 0.004682, Train_acc: 1.000000 Epoch:3, train_step: 3286, loss: 0.003527, Train_acc: 1.000000 Epoch:3, train_step: 3287, loss: 0.001780, Train_acc: 1.000000 Epoch:3, train_step: 3288, loss: 0.007286, Train_acc: 1.000000 Epoch:3, train_step: 3289, loss: 0.001551, Train_acc: 1.000000 Epoch:3, train_step: 3290, loss: 0.014611, Train_acc: 1.000000 Epoch:3, train_step: 3291, loss: 0.002641, Train_acc: 1.000000 Epoch:3, train_step: 3292, loss: 0.009549, Train_acc: 1.000000 Epoch:3, train_step: 3293, loss: 0.031522, Train_acc: 0.984375 Epoch:3, train_step: 3294, loss: 0.005324, Train_acc: 1.000000 Epoch:3, train_step: 3295, loss: 0.012000, Train_acc: 1.000000 Epoch:3, train_step: 3296, loss: 0.000561, Train_acc: 1.000000 Epoch:3, train_step: 3297, loss: 0.010454, Train_acc: 1.000000 Epoch:3, train_step: 3298, loss: 0.010109, Train_acc: 1.000000 Epoch:3, train_step: 3299, loss: 0.013063, Train_acc: 1.000000 Epoch:3, train_step: 3300, loss: 0.020215, Train_acc: 1.000000 Epoch:3, train_step: 3301, loss: 0.011389, Train_acc: 1.000000 Epoch:3, train_step: 3302, loss: 0.040782, Train_acc: 0.984375 Epoch:3, train_step: 3303, loss: 0.001713, Train_acc: 1.000000 Epoch:3, train_step: 3304, loss: 0.057851, Train_acc: 0.984375 Epoch:3, train_step: 3305, loss: 0.028952, Train_acc: 0.984375 Epoch:3, train_step: 3306, loss: 0.107912, Train_acc: 0.953125 Epoch:3, train_step: 3307, loss: 0.009589, Train_acc: 1.000000 Epoch:3, train_step: 3308, loss: 0.012886, Train_acc: 0.984375 Epoch:3, train_step: 3309, loss: 0.033919, Train_acc: 0.984375 Epoch:3, train_step: 3310, loss: 0.022793, Train_acc: 0.984375 Epoch:3, train_step: 3311, loss: 0.020269, Train_acc: 1.000000 Epoch:3, train_step: 3312, loss: 0.020684, Train_acc: 1.000000 Epoch:3, train_step: 3313, loss: 0.055785, Train_acc: 0.968750 Epoch:3, train_step: 3314, loss: 0.006859, Train_acc: 1.000000 Epoch:3, train_step: 3315, loss: 0.005094, Train_acc: 1.000000 Epoch:3, train_step: 3316, loss: 0.002065, Train_acc: 1.000000 Epoch:3, train_step: 3317, loss: 0.207846, Train_acc: 0.968750 Epoch:3, train_step: 3318, loss: 0.017185, Train_acc: 1.000000 Epoch:3, train_step: 3319, loss: 0.052683, Train_acc: 0.984375 Epoch:3, train_step: 3320, loss: 0.024668, Train_acc: 0.984375 Epoch:3, train_step: 3321, loss: 0.003039, Train_acc: 1.000000 Epoch:3, train_step: 3322, loss: 0.008467, Train_acc: 1.000000 Epoch:3, train_step: 3323, loss: 0.013119, Train_acc: 1.000000 Epoch:3, train_step: 3324, loss: 0.002464, Train_acc: 1.000000 Epoch:3, train_step: 3325, loss: 0.015899, Train_acc: 1.000000 Epoch:3, train_step: 3326, loss: 0.002263, Train_acc: 1.000000 Epoch:3, train_step: 3327, loss: 0.000894, Train_acc: 1.000000 Epoch:3, train_step: 3328, loss: 0.006110, Train_acc: 1.000000 Epoch:3, train_step: 3329, loss: 0.002006, Train_acc: 1.000000 Epoch:3, train_step: 3330, loss: 0.005732, Train_acc: 1.000000 Epoch:3, train_step: 3331, loss: 0.003329, Train_acc: 1.000000 Epoch:3, train_step: 3332, loss: 0.024832, Train_acc: 0.984375 Epoch:3, train_step: 3333, loss: 0.030737, Train_acc: 0.984375 Epoch:3, train_step: 3334, loss: 0.027251, Train_acc: 1.000000 Epoch:3, train_step: 3335, loss: 0.017123, Train_acc: 0.984375 Epoch:3, train_step: 3336, loss: 0.042726, Train_acc: 0.984375 Epoch:3, train_step: 3337, loss: 0.031542, Train_acc: 0.984375 Epoch:3, train_step: 3338, loss: 0.002851, Train_acc: 1.000000 Epoch:3, train_step: 3339, loss: 0.077716, Train_acc: 0.984375 Epoch:3, train_step: 3340, loss: 0.001083, Train_acc: 1.000000 Epoch:3, train_step: 3341, loss: 0.002455, Train_acc: 1.000000 Epoch:3, train_step: 3342, loss: 0.000427, Train_acc: 1.000000 Epoch:3, train_step: 3343, loss: 0.003546, Train_acc: 1.000000 Epoch:3, train_step: 3344, loss: 0.013217, Train_acc: 0.984375 Epoch:3, train_step: 3345, loss: 0.005360, Train_acc: 1.000000 Epoch:3, train_step: 3346, loss: 0.007265, Train_acc: 1.000000 Epoch:3, train_step: 3347, loss: 0.000391, Train_acc: 1.000000 Epoch:3, train_step: 3348, loss: 0.002925, Train_acc: 1.000000 Epoch:3, train_step: 3349, loss: 0.116730, Train_acc: 0.968750 Epoch:3, train_step: 3350, loss: 0.024292, Train_acc: 1.000000 Epoch:3, train_step: 3351, loss: 0.003245, Train_acc: 1.000000 Epoch:3, train_step: 3352, loss: 0.005927, Train_acc: 1.000000 Epoch:3, train_step: 3353, loss: 0.075903, Train_acc: 0.984375 Epoch:3, train_step: 3354, loss: 0.087952, Train_acc: 0.968750 Epoch:3, train_step: 3355, loss: 0.006081, Train_acc: 1.000000 Epoch:3, train_step: 3356, loss: 0.057746, Train_acc: 0.984375 Epoch:3, train_step: 3357, loss: 0.072047, Train_acc: 0.984375 Epoch:3, train_step: 3358, loss: 0.001860, Train_acc: 1.000000 Epoch:3, train_step: 3359, loss: 0.050524, Train_acc: 0.984375 Epoch:3, train_step: 3360, loss: 0.002035, Train_acc: 1.000000 Epoch:3, train_step: 3361, loss: 0.086379, Train_acc: 0.984375 Epoch:3, train_step: 3362, loss: 0.085631, Train_acc: 0.984375 Epoch:3, train_step: 3363, loss: 0.063310, Train_acc: 0.968750 Epoch:3, train_step: 3364, loss: 0.018726, Train_acc: 1.000000 Epoch:3, train_step: 3365, loss: 0.003236, Train_acc: 1.000000 Epoch:3, train_step: 3366, loss: 0.077643, Train_acc: 0.984375 Epoch:3, train_step: 3367, loss: 0.011742, Train_acc: 1.000000 Epoch:3, train_step: 3368, loss: 0.080029, Train_acc: 0.984375 Epoch:3, train_step: 3369, loss: 0.011602, Train_acc: 1.000000 Epoch:3, train_step: 3370, loss: 0.020171, Train_acc: 0.984375 Epoch:3, train_step: 3371, loss: 0.002008, Train_acc: 1.000000 Epoch:3, train_step: 3372, loss: 0.002622, Train_acc: 1.000000 Epoch:3, train_step: 3373, loss: 0.032644, Train_acc: 0.984375 Epoch:3, train_step: 3374, loss: 0.020032, Train_acc: 1.000000 Epoch:3, train_step: 3375, loss: 0.002159, Train_acc: 1.000000 Epoch:3, train_step: 3376, loss: 0.018735, Train_acc: 0.984375 Epoch:3, train_step: 3377, loss: 0.054122, Train_acc: 0.984375 Epoch:3, train_step: 3378, loss: 0.012850, Train_acc: 1.000000 Epoch:3, train_step: 3379, loss: 0.000641, Train_acc: 1.000000 Epoch:3, train_step: 3380, loss: 0.001064, Train_acc: 1.000000 Epoch:3, train_step: 3381, loss: 0.029851, Train_acc: 0.984375 Epoch:3, train_step: 3382, loss: 0.001986, Train_acc: 1.000000 Epoch:3, train_step: 3383, loss: 0.002916, Train_acc: 1.000000 Epoch:3, train_step: 3384, loss: 0.009659, Train_acc: 1.000000 Epoch:3, train_step: 3385, loss: 0.060704, Train_acc: 0.968750 Epoch:3, train_step: 3386, loss: 0.047589, Train_acc: 0.984375 Epoch:3, train_step: 3387, loss: 0.008218, Train_acc: 1.000000 Epoch:3, train_step: 3388, loss: 0.003183, Train_acc: 1.000000 Epoch:3, train_step: 3389, loss: 0.057433, Train_acc: 0.968750 Epoch:3, train_step: 3390, loss: 0.102543, Train_acc: 0.984375 Epoch:3, train_step: 3391, loss: 0.023542, Train_acc: 0.984375 Epoch:3, train_step: 3392, loss: 0.028992, Train_acc: 0.984375 Epoch:3, train_step: 3393, loss: 0.003987, Train_acc: 1.000000 Epoch:3, train_step: 3394, loss: 0.002509, Train_acc: 1.000000 Epoch:3, train_step: 3395, loss: 0.012200, Train_acc: 1.000000 Epoch:3, train_step: 3396, loss: 0.060804, Train_acc: 0.984375 Epoch:3, train_step: 3397, loss: 0.014654, Train_acc: 1.000000 Epoch:3, train_step: 3398, loss: 0.029684, Train_acc: 0.984375 Epoch:3, train_step: 3399, loss: 0.001429, Train_acc: 1.000000 Epoch:3, train_step: 3400, loss: 0.036176, Train_acc: 0.984375 Epoch:3, train_step: 3401, loss: 0.026866, Train_acc: 0.984375 Epoch:3, train_step: 3402, loss: 0.016525, Train_acc: 0.984375 Epoch:3, train_step: 3403, loss: 0.055462, Train_acc: 0.968750 Epoch:3, train_step: 3404, loss: 0.004179, Train_acc: 1.000000 Epoch:3, train_step: 3405, loss: 0.009383, Train_acc: 1.000000 Epoch:3, train_step: 3406, loss: 0.006722, Train_acc: 1.000000 Epoch:3, train_step: 3407, loss: 0.006345, Train_acc: 1.000000 Epoch:3, train_step: 3408, loss: 0.011016, Train_acc: 1.000000 Epoch:3, train_step: 3409, loss: 0.004491, Train_acc: 1.000000 Epoch:3, train_step: 3410, loss: 0.008016, Train_acc: 1.000000 Epoch:3, train_step: 3411, loss: 0.019681, Train_acc: 0.984375 Epoch:3, train_step: 3412, loss: 0.056853, Train_acc: 0.984375 Epoch:3, train_step: 3413, loss: 0.041299, Train_acc: 0.984375 Epoch:3, train_step: 3414, loss: 0.002303, Train_acc: 1.000000 Epoch:3, train_step: 3415, loss: 0.029460, Train_acc: 0.984375 Epoch:3, train_step: 3416, loss: 0.125214, Train_acc: 0.984375 Epoch:3, train_step: 3417, loss: 0.005505, Train_acc: 1.000000 Epoch:3, train_step: 3418, loss: 0.000939, Train_acc: 1.000000 Epoch:3, train_step: 3419, loss: 0.013438, Train_acc: 0.984375 Epoch:3, train_step: 3420, loss: 0.021005, Train_acc: 0.984375 Epoch:3, train_step: 3421, loss: 0.005116, Train_acc: 1.000000 Epoch:3, train_step: 3422, loss: 0.001328, Train_acc: 1.000000 Epoch:3, train_step: 3423, loss: 0.002469, Train_acc: 1.000000 Epoch:3, train_step: 3424, loss: 0.022188, Train_acc: 0.984375 Epoch:3, train_step: 3425, loss: 0.040707, Train_acc: 0.968750 Epoch:3, train_step: 3426, loss: 0.017006, Train_acc: 1.000000 Epoch:3, train_step: 3427, loss: 0.055957, Train_acc: 0.968750 Epoch:3, train_step: 3428, loss: 0.009676, Train_acc: 1.000000 Epoch:3, train_step: 3429, loss: 0.040108, Train_acc: 0.984375 Epoch:3, train_step: 3430, loss: 0.011478, Train_acc: 1.000000 Epoch:3, train_step: 3431, loss: 0.045981, Train_acc: 0.968750 Epoch:3, train_step: 3432, loss: 0.068355, Train_acc: 0.968750 Epoch:3, train_step: 3433, loss: 0.125240, Train_acc: 0.953125 Epoch:3, train_step: 3434, loss: 0.065404, Train_acc: 0.984375 Epoch:3, train_step: 3435, loss: 0.033929, Train_acc: 0.984375 Epoch:3, train_step: 3436, loss: 0.013083, Train_acc: 1.000000 Epoch:3, train_step: 3437, loss: 0.100765, Train_acc: 0.968750 Epoch:3, train_step: 3438, loss: 0.014462, Train_acc: 1.000000 Epoch:3, train_step: 3439, loss: 0.145461, Train_acc: 0.984375 Epoch:3, train_step: 3440, loss: 0.008372, Train_acc: 1.000000 Epoch:3, train_step: 3441, loss: 0.037937, Train_acc: 0.984375 Epoch:3, train_step: 3442, loss: 0.009948, Train_acc: 1.000000 Epoch:3, train_step: 3443, loss: 0.037601, Train_acc: 0.984375 Epoch:3, train_step: 3444, loss: 0.001879, Train_acc: 1.000000 Epoch:3, train_step: 3445, loss: 0.011205, Train_acc: 1.000000 Epoch:3, train_step: 3446, loss: 0.033283, Train_acc: 0.984375 Epoch:3, train_step: 3447, loss: 0.007421, Train_acc: 1.000000 Epoch:3, train_step: 3448, loss: 0.012800, Train_acc: 1.000000 Epoch:3, train_step: 3449, loss: 0.000953, Train_acc: 1.000000 Epoch:3, train_step: 3450, loss: 0.045196, Train_acc: 0.984375 Epoch:3, train_step: 3451, loss: 0.038302, Train_acc: 0.984375 Epoch:3, train_step: 3452, loss: 0.090402, Train_acc: 0.984375 Epoch:3, train_step: 3453, loss: 0.047078, Train_acc: 0.984375 Epoch:3, train_step: 3454, loss: 0.001964, Train_acc: 1.000000 Epoch:3, train_step: 3455, loss: 0.059411, Train_acc: 0.984375 Epoch:3, train_step: 3456, loss: 0.011870, Train_acc: 1.000000 Epoch:3, train_step: 3457, loss: 0.047140, Train_acc: 0.968750 Epoch:3, train_step: 3458, loss: 0.008731, Train_acc: 1.000000 Epoch:3, train_step: 3459, loss: 0.007091, Train_acc: 1.000000 Epoch:3, train_step: 3460, loss: 0.029712, Train_acc: 0.984375 Epoch:3, train_step: 3461, loss: 0.019429, Train_acc: 0.984375 Epoch:3, train_step: 3462, loss: 0.046790, Train_acc: 0.984375 Epoch:3, train_step: 3463, loss: 0.014200, Train_acc: 1.000000 Epoch:3, train_step: 3464, loss: 0.026944, Train_acc: 0.984375 Epoch:3, train_step: 3465, loss: 0.057439, Train_acc: 0.968750 Epoch:3, train_step: 3466, loss: 0.070171, Train_acc: 0.984375 Epoch:3, train_step: 3467, loss: 0.016617, Train_acc: 0.984375 Epoch:3, train_step: 3468, loss: 0.050220, Train_acc: 0.984375 Epoch:3, train_step: 3469, loss: 0.019480, Train_acc: 0.984375 Epoch:3, train_step: 3470, loss: 0.007875, Train_acc: 1.000000 Epoch:3, train_step: 3471, loss: 0.008867, Train_acc: 1.000000 Epoch:3, train_step: 3472, loss: 0.022392, Train_acc: 0.984375 Epoch:3, train_step: 3473, loss: 0.010857, Train_acc: 1.000000 Epoch:3, train_step: 3474, loss: 0.019136, Train_acc: 0.984375 Epoch:3, train_step: 3475, loss: 0.060328, Train_acc: 0.968750 Epoch:3, train_step: 3476, loss: 0.002726, Train_acc: 1.000000 Epoch:3, train_step: 3477, loss: 0.083782, Train_acc: 0.984375 Epoch:3, train_step: 3478, loss: 0.035029, Train_acc: 0.984375 Epoch:3, train_step: 3479, loss: 0.006837, Train_acc: 1.000000 Epoch:3, train_step: 3480, loss: 0.023962, Train_acc: 0.984375 Epoch:3, train_step: 3481, loss: 0.047681, Train_acc: 0.984375 Epoch:3, train_step: 3482, loss: 0.022982, Train_acc: 0.984375 Epoch:3, train_step: 3483, loss: 0.045129, Train_acc: 0.984375 Epoch:3, train_step: 3484, loss: 0.008221, Train_acc: 1.000000 Epoch:3, train_step: 3485, loss: 0.169614, Train_acc: 0.984375 Epoch:3, train_step: 3486, loss: 0.009614, Train_acc: 1.000000 Epoch:3, train_step: 3487, loss: 0.018673, Train_acc: 0.984375 Epoch:3, train_step: 3488, loss: 0.001813, Train_acc: 1.000000 Epoch:3, train_step: 3489, loss: 0.003510, Train_acc: 1.000000 Epoch:3, train_step: 3490, loss: 0.157449, Train_acc: 0.984375 Epoch:3, train_step: 3491, loss: 0.033189, Train_acc: 0.984375 Epoch:3, train_step: 3492, loss: 0.010472, Train_acc: 1.000000 Epoch:3, train_step: 3493, loss: 0.015295, Train_acc: 1.000000 Epoch:3, train_step: 3494, loss: 0.128278, Train_acc: 0.968750 Epoch:3, train_step: 3495, loss: 0.009319, Train_acc: 1.000000 Epoch:3, train_step: 3496, loss: 0.002804, Train_acc: 1.000000 Epoch:3, train_step: 3497, loss: 0.014783, Train_acc: 1.000000 Epoch:3, train_step: 3498, loss: 0.012453, Train_acc: 1.000000 Epoch:3, train_step: 3499, loss: 0.005992, Train_acc: 1.000000 Epoch:3, train_step: 3500, loss: 0.017028, Train_acc: 1.000000 Epoch:3, train_step: 3501, loss: 0.002587, Train_acc: 1.000000 Epoch:3, train_step: 3502, loss: 0.004360, Train_acc: 1.000000 Epoch:3, train_step: 3503, loss: 0.015368, Train_acc: 0.984375 Epoch:3, train_step: 3504, loss: 0.002319, Train_acc: 1.000000 Epoch:3, train_step: 3505, loss: 0.003446, Train_acc: 1.000000 Epoch:3, train_step: 3506, loss: 0.048338, Train_acc: 0.953125 Epoch:3, train_step: 3507, loss: 0.005012, Train_acc: 1.000000 Epoch:3, train_step: 3508, loss: 0.013851, Train_acc: 0.984375 Epoch:3, train_step: 3509, loss: 0.002435, Train_acc: 1.000000 Epoch:3, train_step: 3510, loss: 0.021992, Train_acc: 0.984375 Epoch:3, train_step: 3511, loss: 0.016325, Train_acc: 0.984375 Epoch:3, train_step: 3512, loss: 0.018945, Train_acc: 1.000000 Epoch:3, train_step: 3513, loss: 0.004791, Train_acc: 1.000000 Epoch:3, train_step: 3514, loss: 0.003272, Train_acc: 1.000000 Epoch:3, train_step: 3515, loss: 0.009965, Train_acc: 1.000000 Epoch:3, train_step: 3516, loss: 0.005432, Train_acc: 1.000000 Epoch:3, train_step: 3517, loss: 0.054442, Train_acc: 0.984375 Epoch:3, train_step: 3518, loss: 0.001071, Train_acc: 1.000000 Epoch:3, train_step: 3519, loss: 0.001769, Train_acc: 1.000000 Epoch:3, train_step: 3520, loss: 0.108289, Train_acc: 0.984375 Epoch:3, train_step: 3521, loss: 0.024629, Train_acc: 0.984375 Epoch:3, train_step: 3522, loss: 0.002499, Train_acc: 1.000000 Epoch:3, train_step: 3523, loss: 0.025666, Train_acc: 0.984375 Epoch:3, train_step: 3524, loss: 0.046246, Train_acc: 0.968750 Epoch:3, train_step: 3525, loss: 0.005731, Train_acc: 1.000000 Epoch:3, train_step: 3526, loss: 0.000976, Train_acc: 1.000000 Epoch:3, train_step: 3527, loss: 0.005119, Train_acc: 1.000000 Epoch:3, train_step: 3528, loss: 0.057528, Train_acc: 0.984375 Epoch:3, train_step: 3529, loss: 0.013686, Train_acc: 1.000000 Epoch:3, train_step: 3530, loss: 0.061855, Train_acc: 0.968750 Epoch:3, train_step: 3531, loss: 0.089414, Train_acc: 0.953125 Epoch:3, train_step: 3532, loss: 0.040892, Train_acc: 0.984375 Epoch:3, train_step: 3533, loss: 0.003701, Train_acc: 1.000000 Epoch:3, train_step: 3534, loss: 0.035454, Train_acc: 1.000000 Epoch:3, train_step: 3535, loss: 0.017335, Train_acc: 1.000000 Epoch:3, train_step: 3536, loss: 0.020589, Train_acc: 0.984375 Epoch:3, train_step: 3537, loss: 0.022077, Train_acc: 0.984375 Epoch:3, train_step: 3538, loss: 0.004296, Train_acc: 1.000000 Epoch:3, train_step: 3539, loss: 0.003653, Train_acc: 1.000000 Epoch:3, train_step: 3540, loss: 0.003754, Train_acc: 1.000000 Epoch:3, train_step: 3541, loss: 0.026213, Train_acc: 0.984375 Epoch:3, train_step: 3542, loss: 0.011353, Train_acc: 1.000000 Epoch:3, train_step: 3543, loss: 0.023529, Train_acc: 0.984375 Epoch:3, train_step: 3544, loss: 0.075060, Train_acc: 0.984375 Epoch:3, train_step: 3545, loss: 0.006162, Train_acc: 1.000000 Epoch:3, train_step: 3546, loss: 0.028549, Train_acc: 0.984375 Epoch:3, train_step: 3547, loss: 0.026468, Train_acc: 0.984375 Epoch:3, train_step: 3548, loss: 0.006475, Train_acc: 1.000000 Epoch:3, train_step: 3549, loss: 0.024775, Train_acc: 0.984375 Epoch:3, train_step: 3550, loss: 0.056244, Train_acc: 0.984375 Epoch:3, train_step: 3551, loss: 0.020520, Train_acc: 0.984375 Epoch:3, train_step: 3552, loss: 0.031243, Train_acc: 0.968750 Epoch:3, train_step: 3553, loss: 0.018615, Train_acc: 1.000000 Epoch:3, train_step: 3554, loss: 0.015151, Train_acc: 1.000000 Epoch:3, train_step: 3555, loss: 0.045178, Train_acc: 0.984375 Epoch:3, train_step: 3556, loss: 0.005738, Train_acc: 1.000000 Epoch:3, train_step: 3557, loss: 0.012387, Train_acc: 1.000000 Epoch:3, train_step: 3558, loss: 0.011854, Train_acc: 1.000000 Epoch:3, train_step: 3559, loss: 0.008679, Train_acc: 1.000000 Epoch:3, train_step: 3560, loss: 0.014260, Train_acc: 1.000000 Epoch:3, train_step: 3561, loss: 0.016838, Train_acc: 1.000000 Epoch:3, train_step: 3562, loss: 0.004001, Train_acc: 1.000000 Epoch:3, train_step: 3563, loss: 0.040730, Train_acc: 0.984375 Epoch:3, train_step: 3564, loss: 0.003705, Train_acc: 1.000000 Epoch:3, train_step: 3565, loss: 0.022379, Train_acc: 0.984375 Epoch:3, train_step: 3566, loss: 0.014095, Train_acc: 1.000000 Epoch:3, train_step: 3567, loss: 0.013181, Train_acc: 1.000000 Epoch:3, train_step: 3568, loss: 0.004782, Train_acc: 1.000000 Epoch:3, train_step: 3569, loss: 0.039184, Train_acc: 0.984375 Epoch:3, train_step: 3570, loss: 0.010487, Train_acc: 1.000000 Epoch:3, train_step: 3571, loss: 0.007957, Train_acc: 1.000000 Epoch:3, train_step: 3572, loss: 0.008163, Train_acc: 1.000000 Epoch:3, train_step: 3573, loss: 0.007152, Train_acc: 1.000000 Epoch:3, train_step: 3574, loss: 0.008834, Train_acc: 1.000000 Epoch:3, train_step: 3575, loss: 0.010827, Train_acc: 1.000000 Epoch:3, train_step: 3576, loss: 0.014206, Train_acc: 1.000000 Epoch:3, train_step: 3577, loss: 0.035397, Train_acc: 0.984375 Epoch:3, train_step: 3578, loss: 0.016952, Train_acc: 1.000000 Epoch:3, train_step: 3579, loss: 0.015390, Train_acc: 0.984375 Epoch:3, train_step: 3580, loss: 0.052079, Train_acc: 0.984375 Epoch:3, train_step: 3581, loss: 0.002746, Train_acc: 1.000000 Epoch:3, train_step: 3582, loss: 0.002101, Train_acc: 1.000000 Epoch:3, train_step: 3583, loss: 0.003872, Train_acc: 1.000000 Epoch:3, train_step: 3584, loss: 0.052345, Train_acc: 0.968750 Epoch:3, train_step: 3585, loss: 0.026411, Train_acc: 1.000000 Epoch:3, train_step: 3586, loss: 0.019477, Train_acc: 1.000000 Epoch:3, train_step: 3587, loss: 0.004786, Train_acc: 1.000000 Epoch:3, train_step: 3588, loss: 0.009234, Train_acc: 1.000000 Epoch:3, train_step: 3589, loss: 0.028939, Train_acc: 1.000000 Epoch:3, train_step: 3590, loss: 0.015030, Train_acc: 0.984375 Epoch:3, train_step: 3591, loss: 0.039156, Train_acc: 0.984375 Epoch:3, train_step: 3592, loss: 0.004045, Train_acc: 1.000000 Epoch:3, train_step: 3593, loss: 0.011009, Train_acc: 1.000000 Epoch:3, train_step: 3594, loss: 0.002532, Train_acc: 1.000000 Epoch:3, train_step: 3595, loss: 0.023843, Train_acc: 0.984375 Epoch:3, train_step: 3596, loss: 0.013181, Train_acc: 1.000000 Epoch:3, train_step: 3597, loss: 0.002159, Train_acc: 1.000000 Epoch:3, train_step: 3598, loss: 0.025913, Train_acc: 0.984375 Epoch:3, train_step: 3599, loss: 0.013717, Train_acc: 1.000000 Epoch:3, train_step: 3600, loss: 0.008331, Train_acc: 1.000000 Epoch:3, train_step: 3601, loss: 0.003211, Train_acc: 1.000000 Epoch:3, train_step: 3602, loss: 0.016378, Train_acc: 1.000000 Epoch:3, train_step: 3603, loss: 0.000323, Train_acc: 1.000000 Epoch:3, train_step: 3604, loss: 0.005673, Train_acc: 1.000000 Epoch:3, train_step: 3605, loss: 0.002683, Train_acc: 1.000000 Epoch:3, train_step: 3606, loss: 0.005088, Train_acc: 1.000000 Epoch:3, train_step: 3607, loss: 0.056767, Train_acc: 0.984375 Epoch:3, train_step: 3608, loss: 0.038235, Train_acc: 0.984375 Epoch:3, train_step: 3609, loss: 0.001950, Train_acc: 1.000000 Epoch:3, train_step: 3610, loss: 0.005472, Train_acc: 1.000000 Epoch:3, train_step: 3611, loss: 0.007332, Train_acc: 1.000000 Epoch:3, train_step: 3612, loss: 0.038391, Train_acc: 0.968750 Epoch:3, train_step: 3613, loss: 0.016793, Train_acc: 1.000000 Epoch:3, train_step: 3614, loss: 0.006871, Train_acc: 1.000000 Epoch:3, train_step: 3615, loss: 0.009694, Train_acc: 1.000000 Epoch:3, train_step: 3616, loss: 0.014079, Train_acc: 1.000000 Epoch:3, train_step: 3617, loss: 0.005746, Train_acc: 1.000000 Epoch:3, train_step: 3618, loss: 0.005189, Train_acc: 1.000000 Epoch:3, train_step: 3619, loss: 0.008879, Train_acc: 1.000000 Epoch:3, train_step: 3620, loss: 0.017097, Train_acc: 0.984375 Epoch:3, train_step: 3621, loss: 0.001015, Train_acc: 1.000000 Epoch:3, train_step: 3622, loss: 0.000416, Train_acc: 1.000000 Epoch:3, train_step: 3623, loss: 0.126812, Train_acc: 0.984375 Epoch:3, train_step: 3624, loss: 0.016254, Train_acc: 1.000000 Epoch:3, train_step: 3625, loss: 0.006099, Train_acc: 1.000000 Epoch:3, train_step: 3626, loss: 0.029149, Train_acc: 0.984375 Epoch:3, train_step: 3627, loss: 0.025082, Train_acc: 0.984375 Epoch:3, train_step: 3628, loss: 0.027112, Train_acc: 0.984375 Epoch:3, train_step: 3629, loss: 0.005303, Train_acc: 1.000000 Epoch:3, train_step: 3630, loss: 0.012355, Train_acc: 1.000000 Epoch:3, train_step: 3631, loss: 0.007410, Train_acc: 1.000000 Epoch:3, train_step: 3632, loss: 0.018076, Train_acc: 0.984375 Epoch:3, train_step: 3633, loss: 0.001694, Train_acc: 1.000000 Epoch:3, train_step: 3634, loss: 0.007466, Train_acc: 1.000000 Epoch:3, train_step: 3635, loss: 0.005870, Train_acc: 1.000000 Epoch:3, train_step: 3636, loss: 0.005734, Train_acc: 1.000000 Epoch:3, train_step: 3637, loss: 0.051995, Train_acc: 0.984375 Epoch:3, train_step: 3638, loss: 0.027550, Train_acc: 0.984375 Epoch:3, train_step: 3639, loss: 0.138714, Train_acc: 0.953125 Epoch:3, train_step: 3640, loss: 0.026317, Train_acc: 0.984375 Epoch:3, train_step: 3641, loss: 0.001063, Train_acc: 1.000000 Epoch:3, train_step: 3642, loss: 0.013421, Train_acc: 1.000000 Epoch:3, train_step: 3643, loss: 0.004253, Train_acc: 1.000000 Epoch:3, train_step: 3644, loss: 0.005556, Train_acc: 1.000000 Epoch:3, train_step: 3645, loss: 0.007289, Train_acc: 1.000000 Epoch:3, train_step: 3646, loss: 0.048016, Train_acc: 0.984375 Epoch:3, train_step: 3647, loss: 0.011754, Train_acc: 1.000000 Epoch:3, train_step: 3648, loss: 0.012285, Train_acc: 1.000000 Epoch:3, train_step: 3649, loss: 0.001486, Train_acc: 1.000000 Epoch:3, train_step: 3650, loss: 0.055091, Train_acc: 0.953125 Epoch:3, train_step: 3651, loss: 0.002899, Train_acc: 1.000000 Epoch:3, train_step: 3652, loss: 0.010292, Train_acc: 1.000000 Epoch:3, train_step: 3653, loss: 0.004939, Train_acc: 1.000000 Epoch:3, train_step: 3654, loss: 0.013641, Train_acc: 1.000000 Epoch:3, train_step: 3655, loss: 0.009982, Train_acc: 1.000000 Epoch:3, train_step: 3656, loss: 0.027182, Train_acc: 0.984375 Epoch:3, train_step: 3657, loss: 0.035782, Train_acc: 0.984375 Epoch:3, train_step: 3658, loss: 0.002601, Train_acc: 1.000000 Epoch:3, train_step: 3659, loss: 0.027456, Train_acc: 0.984375 Epoch:3, train_step: 3660, loss: 0.060613, Train_acc: 0.984375 Epoch:3, train_step: 3661, loss: 0.001391, Train_acc: 1.000000 Epoch:3, train_step: 3662, loss: 0.005673, Train_acc: 1.000000 Epoch:3, train_step: 3663, loss: 0.003122, Train_acc: 1.000000 Epoch:3, train_step: 3664, loss: 0.032174, Train_acc: 0.984375 Epoch:3, train_step: 3665, loss: 0.008053, Train_acc: 1.000000 Epoch:3, train_step: 3666, loss: 0.017573, Train_acc: 0.984375 Epoch:3, train_step: 3667, loss: 0.010104, Train_acc: 1.000000 Epoch:3, train_step: 3668, loss: 0.010776, Train_acc: 1.000000 Epoch:3, train_step: 3669, loss: 0.046462, Train_acc: 0.968750 Epoch:3, train_step: 3670, loss: 0.005224, Train_acc: 1.000000 Epoch:3, train_step: 3671, loss: 0.001027, Train_acc: 1.000000 Epoch:3, train_step: 3672, loss: 0.011425, Train_acc: 1.000000 Epoch:3, train_step: 3673, loss: 0.000882, Train_acc: 1.000000 Epoch:3, train_step: 3674, loss: 0.005384, Train_acc: 1.000000 Epoch:3, train_step: 3675, loss: 0.011595, Train_acc: 1.000000 Epoch:3, train_step: 3676, loss: 0.010826, Train_acc: 1.000000 Epoch:3, train_step: 3677, loss: 0.049137, Train_acc: 0.984375 Epoch:3, train_step: 3678, loss: 0.040564, Train_acc: 0.953125 Epoch:3, train_step: 3679, loss: 0.006912, Train_acc: 1.000000 Epoch:3, train_step: 3680, loss: 0.047906, Train_acc: 0.984375 Epoch:3, train_step: 3681, loss: 0.002082, Train_acc: 1.000000 Epoch:3, train_step: 3682, loss: 0.017243, Train_acc: 0.984375 Epoch:3, train_step: 3683, loss: 0.006311, Train_acc: 1.000000 Epoch:3, train_step: 3684, loss: 0.006881, Train_acc: 1.000000 Epoch:3, train_step: 3685, loss: 0.004866, Train_acc: 1.000000 Epoch:3, train_step: 3686, loss: 0.006194, Train_acc: 1.000000 Epoch:3, train_step: 3687, loss: 0.013436, Train_acc: 0.984375 Epoch:3, train_step: 3688, loss: 0.002076, Train_acc: 1.000000 Epoch:3, train_step: 3689, loss: 0.061712, Train_acc: 0.984375 Epoch:3, train_step: 3690, loss: 0.049164, Train_acc: 0.984375 Epoch:3, train_step: 3691, loss: 0.006980, Train_acc: 1.000000 Epoch:3, train_step: 3692, loss: 0.005720, Train_acc: 1.000000 Epoch:3, train_step: 3693, loss: 0.028363, Train_acc: 0.984375 Epoch:3, train_step: 3694, loss: 0.030432, Train_acc: 0.984375 Epoch:3, train_step: 3695, loss: 0.000868, Train_acc: 1.000000 Epoch:3, train_step: 3696, loss: 0.019956, Train_acc: 1.000000 Epoch:3, train_step: 3697, loss: 0.012755, Train_acc: 0.984375 Epoch:3, train_step: 3698, loss: 0.006585, Train_acc: 1.000000 Epoch:3, train_step: 3699, loss: 0.029570, Train_acc: 1.000000 Epoch:3, train_step: 3700, loss: 0.003910, Train_acc: 1.000000 Epoch:3, train_step: 3701, loss: 0.026518, Train_acc: 0.984375 Epoch:3, train_step: 3702, loss: 0.002875, Train_acc: 1.000000 Epoch:3, train_step: 3703, loss: 0.012902, Train_acc: 1.000000 Epoch:3, train_step: 3704, loss: 0.000283, Train_acc: 1.000000 Epoch:3, train_step: 3705, loss: 0.002296, Train_acc: 1.000000 Epoch:3, train_step: 3706, loss: 0.007121, Train_acc: 1.000000 Epoch:3, train_step: 3707, loss: 0.006880, Train_acc: 1.000000 Epoch:3, train_step: 3708, loss: 0.005419, Train_acc: 1.000000 Epoch:3, train_step: 3709, loss: 0.008283, Train_acc: 1.000000 Epoch:3, train_step: 3710, loss: 0.032851, Train_acc: 0.984375 Epoch:3, train_step: 3711, loss: 0.002699, Train_acc: 1.000000 Epoch:3, train_step: 3712, loss: 0.022338, Train_acc: 0.984375 Epoch:3, train_step: 3713, loss: 0.015073, Train_acc: 0.984375 Epoch:3, train_step: 3714, loss: 0.037019, Train_acc: 0.984375 Epoch:3, train_step: 3715, loss: 0.019223, Train_acc: 1.000000 Epoch:3, train_step: 3716, loss: 0.005243, Train_acc: 1.000000 Epoch:3, train_step: 3717, loss: 0.016573, Train_acc: 1.000000 Epoch:3, train_step: 3718, loss: 0.025970, Train_acc: 0.984375 Epoch:3, train_step: 3719, loss: 0.044893, Train_acc: 0.984375 Epoch:3, train_step: 3720, loss: 0.000279, Train_acc: 1.000000 Epoch:3, train_step: 3721, loss: 0.005862, Train_acc: 1.000000 Epoch:3, train_step: 3722, loss: 0.000349, Train_acc: 1.000000 Epoch:3, train_step: 3723, loss: 0.002115, Train_acc: 1.000000 Epoch:3, train_step: 3724, loss: 0.004473, Train_acc: 1.000000 Epoch:3, train_step: 3725, loss: 0.001319, Train_acc: 1.000000 Epoch:3, train_step: 3726, loss: 0.001473, Train_acc: 1.000000 Epoch:3, train_step: 3727, loss: 0.000576, Train_acc: 1.000000 Epoch:3, train_step: 3728, loss: 0.013294, Train_acc: 0.984375 Epoch:3, train_step: 3729, loss: 0.000040, Train_acc: 1.000000 Epoch:3, train_step: 3730, loss: 0.003680, Train_acc: 1.000000 Epoch:3, train_step: 3731, loss: 0.004520, Train_acc: 1.000000 Epoch:3, train_step: 3732, loss: 0.006867, Train_acc: 1.000000 Epoch:3, train_step: 3733, loss: 0.000084, Train_acc: 1.000000 Epoch:3, train_step: 3734, loss: 0.001099, Train_acc: 1.000000 Epoch:3, train_step: 3735, loss: 0.000183, Train_acc: 1.000000 Epoch:3, train_step: 3736, loss: 0.000252, Train_acc: 1.000000 Epoch:3, train_step: 3737, loss: 0.000121, Train_acc: 1.000000 Epoch:3, train_step: 3738, loss: 0.003407, Train_acc: 1.000000 Epoch:3, train_step: 3739, loss: 0.005592, Train_acc: 1.000000 Epoch:3, train_step: 3740, loss: 0.006940, Train_acc: 1.000000 Epoch:3, train_step: 3741, loss: 0.004402, Train_acc: 1.000000 Epoch:3, train_step: 3742, loss: 0.000218, Train_acc: 1.000000 Epoch:3, train_step: 3743, loss: 0.001558, Train_acc: 1.000000 Epoch:3, train_step: 3744, loss: 0.031732, Train_acc: 0.984375 Epoch:3, train_step: 3745, loss: 0.130916, Train_acc: 0.953125 Epoch:3, train_step: 3746, loss: 0.001182, Train_acc: 1.000000 Epoch:3, train_step: 3747, loss: 0.000468, Train_acc: 1.000000 Epoch:3, train_step: 3748, loss: 0.179660, Train_acc: 0.984375 Epoch:3, avg_train_loss: 0.022916, avg_train_acc: 0.993013, Test_acc: 0.985877 Epoch:4, train_step: 3749, loss: 0.009126, Train_acc: 1.000000 Epoch:4, train_step: 3750, loss: 0.024680, Train_acc: 0.984375 Epoch:4, train_step: 3751, loss: 0.147683, Train_acc: 0.968750 Epoch:4, train_step: 3752, loss: 0.023776, Train_acc: 1.000000 Epoch:4, train_step: 3753, loss: 0.003802, Train_acc: 1.000000 Epoch:4, train_step: 3754, loss: 0.007601, Train_acc: 1.000000 Epoch:4, train_step: 3755, loss: 0.042103, Train_acc: 0.984375 Epoch:4, train_step: 3756, loss: 0.125880, Train_acc: 0.968750 Epoch:4, train_step: 3757, loss: 0.012667, Train_acc: 1.000000 Epoch:4, train_step: 3758, loss: 0.052398, Train_acc: 0.968750 Epoch:4, train_step: 3759, loss: 0.003783, Train_acc: 1.000000 Epoch:4, train_step: 3760, loss: 0.021817, Train_acc: 0.984375 Epoch:4, train_step: 3761, loss: 0.058172, Train_acc: 0.968750 Epoch:4, train_step: 3762, loss: 0.014380, Train_acc: 1.000000 Epoch:4, train_step: 3763, loss: 0.053778, Train_acc: 0.984375 Epoch:4, train_step: 3764, loss: 0.053831, Train_acc: 0.968750 Epoch:4, train_step: 3765, loss: 0.017609, Train_acc: 1.000000 Epoch:4, train_step: 3766, loss: 0.021377, Train_acc: 1.000000 Epoch:4, train_step: 3767, loss: 0.025528, Train_acc: 0.984375 Epoch:4, train_step: 3768, loss: 0.002300, Train_acc: 1.000000 Epoch:4, train_step: 3769, loss: 0.015291, Train_acc: 1.000000 Epoch:4, train_step: 3770, loss: 0.067967, Train_acc: 0.968750 Epoch:4, train_step: 3771, loss: 0.000269, Train_acc: 1.000000 Epoch:4, train_step: 3772, loss: 0.002990, Train_acc: 1.000000 Epoch:4, train_step: 3773, loss: 0.004560, Train_acc: 1.000000 Epoch:4, train_step: 3774, loss: 0.127328, Train_acc: 0.968750 Epoch:4, train_step: 3775, loss: 0.004151, Train_acc: 1.000000 Epoch:4, train_step: 3776, loss: 0.021585, Train_acc: 0.984375 Epoch:4, train_step: 3777, loss: 0.032701, Train_acc: 0.984375 Epoch:4, train_step: 3778, loss: 0.001470, Train_acc: 1.000000 Epoch:4, train_step: 3779, loss: 0.015922, Train_acc: 0.984375 Epoch:4, train_step: 3780, loss: 0.007235, Train_acc: 1.000000 Epoch:4, train_step: 3781, loss: 0.003630, Train_acc: 1.000000 Epoch:4, train_step: 3782, loss: 0.003871, Train_acc: 1.000000 Epoch:4, train_step: 3783, loss: 0.017872, Train_acc: 0.984375 Epoch:4, train_step: 3784, loss: 0.002064, Train_acc: 1.000000 Epoch:4, train_step: 3785, loss: 0.001159, Train_acc: 1.000000 Epoch:4, train_step: 3786, loss: 0.037710, Train_acc: 0.984375 Epoch:4, train_step: 3787, loss: 0.000869, Train_acc: 1.000000 Epoch:4, train_step: 3788, loss: 0.018919, Train_acc: 1.000000 Epoch:4, train_step: 3789, loss: 0.018038, Train_acc: 0.984375 Epoch:4, train_step: 3790, loss: 0.034950, Train_acc: 0.984375 Epoch:4, train_step: 3791, loss: 0.121048, Train_acc: 0.953125 Epoch:4, train_step: 3792, loss: 0.005853, Train_acc: 1.000000 Epoch:4, train_step: 3793, loss: 0.007758, Train_acc: 1.000000 Epoch:4, train_step: 3794, loss: 0.009444, Train_acc: 1.000000 Epoch:4, train_step: 3795, loss: 0.004717, Train_acc: 1.000000 Epoch:4, train_step: 3796, loss: 0.011254, Train_acc: 1.000000 Epoch:4, train_step: 3797, loss: 0.004167, Train_acc: 1.000000 Epoch:4, train_step: 3798, loss: 0.000526, Train_acc: 1.000000 Epoch:4, train_step: 3799, loss: 0.074317, Train_acc: 0.984375 Epoch:4, train_step: 3800, loss: 0.016611, Train_acc: 0.984375 Epoch:4, train_step: 3801, loss: 0.000600, Train_acc: 1.000000 Epoch:4, train_step: 3802, loss: 0.006287, Train_acc: 1.000000 Epoch:4, train_step: 3803, loss: 0.010314, Train_acc: 1.000000 Epoch:4, train_step: 3804, loss: 0.008826, Train_acc: 1.000000 Epoch:4, train_step: 3805, loss: 0.002595, Train_acc: 1.000000 Epoch:4, train_step: 3806, loss: 0.202718, Train_acc: 0.953125 Epoch:4, train_step: 3807, loss: 0.033574, Train_acc: 0.984375 Epoch:4, train_step: 3808, loss: 0.005158, Train_acc: 1.000000 Epoch:4, train_step: 3809, loss: 0.003276, Train_acc: 1.000000 Epoch:4, train_step: 3810, loss: 0.020452, Train_acc: 0.984375 Epoch:4, train_step: 3811, loss: 0.005761, Train_acc: 1.000000 Epoch:4, train_step: 3812, loss: 0.003476, Train_acc: 1.000000 Epoch:4, train_step: 3813, loss: 0.027199, Train_acc: 0.984375 Epoch:4, train_step: 3814, loss: 0.002377, Train_acc: 1.000000 Epoch:4, train_step: 3815, loss: 0.009345, Train_acc: 1.000000 Epoch:4, train_step: 3816, loss: 0.019845, Train_acc: 0.984375 Epoch:4, train_step: 3817, loss: 0.018391, Train_acc: 0.984375 Epoch:4, train_step: 3818, loss: 0.068507, Train_acc: 0.984375 Epoch:4, train_step: 3819, loss: 0.001424, Train_acc: 1.000000 Epoch:4, train_step: 3820, loss: 0.003551, Train_acc: 1.000000 Epoch:4, train_step: 3821, loss: 0.011377, Train_acc: 1.000000 Epoch:4, train_step: 3822, loss: 0.005842, Train_acc: 1.000000 Epoch:4, train_step: 3823, loss: 0.002848, Train_acc: 1.000000 Epoch:4, train_step: 3824, loss: 0.008482, Train_acc: 1.000000 Epoch:4, train_step: 3825, loss: 0.000652, Train_acc: 1.000000 Epoch:4, train_step: 3826, loss: 0.004725, Train_acc: 1.000000 Epoch:4, train_step: 3827, loss: 0.020289, Train_acc: 1.000000 Epoch:4, train_step: 3828, loss: 0.008885, Train_acc: 1.000000 Epoch:4, train_step: 3829, loss: 0.048011, Train_acc: 0.984375 Epoch:4, train_step: 3830, loss: 0.001330, Train_acc: 1.000000 Epoch:4, train_step: 3831, loss: 0.009058, Train_acc: 1.000000 Epoch:4, train_step: 3832, loss: 0.017301, Train_acc: 1.000000 Epoch:4, train_step: 3833, loss: 0.013082, Train_acc: 0.984375 Epoch:4, train_step: 3834, loss: 0.010526, Train_acc: 1.000000 Epoch:4, train_step: 3835, loss: 0.004610, Train_acc: 1.000000 Epoch:4, train_step: 3836, loss: 0.002725, Train_acc: 1.000000 Epoch:4, train_step: 3837, loss: 0.016851, Train_acc: 1.000000 Epoch:4, train_step: 3838, loss: 0.033385, Train_acc: 0.984375 Epoch:4, train_step: 3839, loss: 0.068854, Train_acc: 0.984375 Epoch:4, train_step: 3840, loss: 0.013426, Train_acc: 1.000000 Epoch:4, train_step: 3841, loss: 0.012987, Train_acc: 1.000000 Epoch:4, train_step: 3842, loss: 0.002608, Train_acc: 1.000000 Epoch:4, train_step: 3843, loss: 0.001999, Train_acc: 1.000000 Epoch:4, train_step: 3844, loss: 0.004619, Train_acc: 1.000000 Epoch:4, train_step: 3845, loss: 0.001190, Train_acc: 1.000000 Epoch:4, train_step: 3846, loss: 0.023257, Train_acc: 0.984375 Epoch:4, train_step: 3847, loss: 0.010008, Train_acc: 1.000000 Epoch:4, train_step: 3848, loss: 0.031431, Train_acc: 0.984375 Epoch:4, train_step: 3849, loss: 0.018297, Train_acc: 0.984375 Epoch:4, train_step: 3850, loss: 0.002126, Train_acc: 1.000000 Epoch:4, train_step: 3851, loss: 0.004379, Train_acc: 1.000000 Epoch:4, train_step: 3852, loss: 0.003585, Train_acc: 1.000000 Epoch:4, train_step: 3853, loss: 0.019178, Train_acc: 0.984375 Epoch:4, train_step: 3854, loss: 0.000451, Train_acc: 1.000000 Epoch:4, train_step: 3855, loss: 0.006900, Train_acc: 1.000000 Epoch:4, train_step: 3856, loss: 0.025544, Train_acc: 1.000000 Epoch:4, train_step: 3857, loss: 0.012530, Train_acc: 1.000000 Epoch:4, train_step: 3858, loss: 0.019580, Train_acc: 1.000000 Epoch:4, train_step: 3859, loss: 0.076388, Train_acc: 0.984375 Epoch:4, train_step: 3860, loss: 0.000604, Train_acc: 1.000000 Epoch:4, train_step: 3861, loss: 0.007579, Train_acc: 1.000000 Epoch:4, train_step: 3862, loss: 0.195476, Train_acc: 0.953125 Epoch:4, train_step: 3863, loss: 0.006039, Train_acc: 1.000000 Epoch:4, train_step: 3864, loss: 0.007283, Train_acc: 1.000000 Epoch:4, train_step: 3865, loss: 0.015907, Train_acc: 1.000000 Epoch:4, train_step: 3866, loss: 0.013118, Train_acc: 0.984375 Epoch:4, train_step: 3867, loss: 0.058937, Train_acc: 0.984375 Epoch:4, train_step: 3868, loss: 0.032562, Train_acc: 0.984375 Epoch:4, train_step: 3869, loss: 0.005385, Train_acc: 1.000000 Epoch:4, train_step: 3870, loss: 0.015783, Train_acc: 1.000000 Epoch:4, train_step: 3871, loss: 0.025936, Train_acc: 0.984375 Epoch:4, train_step: 3872, loss: 0.003515, Train_acc: 1.000000 Epoch:4, train_step: 3873, loss: 0.015709, Train_acc: 1.000000 Epoch:4, train_step: 3874, loss: 0.044345, Train_acc: 0.968750 Epoch:4, train_step: 3875, loss: 0.027316, Train_acc: 0.984375 Epoch:4, train_step: 3876, loss: 0.002417, Train_acc: 1.000000 Epoch:4, train_step: 3877, loss: 0.010993, Train_acc: 1.000000 Epoch:4, train_step: 3878, loss: 0.019369, Train_acc: 1.000000 Epoch:4, train_step: 3879, loss: 0.005284, Train_acc: 1.000000 Epoch:4, train_step: 3880, loss: 0.001560, Train_acc: 1.000000 Epoch:4, train_step: 3881, loss: 0.083826, Train_acc: 0.984375 Epoch:4, train_step: 3882, loss: 0.008891, Train_acc: 1.000000 Epoch:4, train_step: 3883, loss: 0.006183, Train_acc: 1.000000 Epoch:4, train_step: 3884, loss: 0.010905, Train_acc: 1.000000 Epoch:4, train_step: 3885, loss: 0.019896, Train_acc: 0.984375 Epoch:4, train_step: 3886, loss: 0.008962, Train_acc: 1.000000 Epoch:4, train_step: 3887, loss: 0.040979, Train_acc: 0.984375 Epoch:4, train_step: 3888, loss: 0.024556, Train_acc: 0.984375 Epoch:4, train_step: 3889, loss: 0.002408, Train_acc: 1.000000 Epoch:4, train_step: 3890, loss: 0.008165, Train_acc: 1.000000 Epoch:4, train_step: 3891, loss: 0.009086, Train_acc: 1.000000 Epoch:4, train_step: 3892, loss: 0.001273, Train_acc: 1.000000 Epoch:4, train_step: 3893, loss: 0.012604, Train_acc: 1.000000 Epoch:4, train_step: 3894, loss: 0.004210, Train_acc: 1.000000 Epoch:4, train_step: 3895, loss: 0.007786, Train_acc: 1.000000 Epoch:4, train_step: 3896, loss: 0.021213, Train_acc: 0.984375 Epoch:4, train_step: 3897, loss: 0.020566, Train_acc: 0.984375 Epoch:4, train_step: 3898, loss: 0.001598, Train_acc: 1.000000 Epoch:4, train_step: 3899, loss: 0.006599, Train_acc: 1.000000 Epoch:4, train_step: 3900, loss: 0.018506, Train_acc: 1.000000 Epoch:4, train_step: 3901, loss: 0.045926, Train_acc: 0.984375 Epoch:4, train_step: 3902, loss: 0.000559, Train_acc: 1.000000 Epoch:4, train_step: 3903, loss: 0.001798, Train_acc: 1.000000 Epoch:4, train_step: 3904, loss: 0.009775, Train_acc: 1.000000 Epoch:4, train_step: 3905, loss: 0.001249, Train_acc: 1.000000 Epoch:4, train_step: 3906, loss: 0.042803, Train_acc: 0.984375 Epoch:4, train_step: 3907, loss: 0.010318, Train_acc: 1.000000 Epoch:4, train_step: 3908, loss: 0.008750, Train_acc: 1.000000 Epoch:4, train_step: 3909, loss: 0.057307, Train_acc: 0.984375 Epoch:4, train_step: 3910, loss: 0.004126, Train_acc: 1.000000 Epoch:4, train_step: 3911, loss: 0.015003, Train_acc: 0.984375 Epoch:4, train_step: 3912, loss: 0.001212, Train_acc: 1.000000 Epoch:4, train_step: 3913, loss: 0.000354, Train_acc: 1.000000 Epoch:4, train_step: 3914, loss: 0.002507, Train_acc: 1.000000 Epoch:4, train_step: 3915, loss: 0.001768, Train_acc: 1.000000 Epoch:4, train_step: 3916, loss: 0.005022, Train_acc: 1.000000 Epoch:4, train_step: 3917, loss: 0.017042, Train_acc: 1.000000 Epoch:4, train_step: 3918, loss: 0.004758, Train_acc: 1.000000 Epoch:4, train_step: 3919, loss: 0.002490, Train_acc: 1.000000 Epoch:4, train_step: 3920, loss: 0.165716, Train_acc: 0.968750 Epoch:4, train_step: 3921, loss: 0.004756, Train_acc: 1.000000 Epoch:4, train_step: 3922, loss: 0.001965, Train_acc: 1.000000 Epoch:4, train_step: 3923, loss: 0.001896, Train_acc: 1.000000 Epoch:4, train_step: 3924, loss: 0.113925, Train_acc: 0.984375 Epoch:4, train_step: 3925, loss: 0.003475, Train_acc: 1.000000 Epoch:4, train_step: 3926, loss: 0.045416, Train_acc: 0.984375 Epoch:4, train_step: 3927, loss: 0.001983, Train_acc: 1.000000 Epoch:4, train_step: 3928, loss: 0.001688, Train_acc: 1.000000 Epoch:4, train_step: 3929, loss: 0.002801, Train_acc: 1.000000 Epoch:4, train_step: 3930, loss: 0.002527, Train_acc: 1.000000 Epoch:4, train_step: 3931, loss: 0.004731, Train_acc: 1.000000 Epoch:4, train_step: 3932, loss: 0.002948, Train_acc: 1.000000 Epoch:4, train_step: 3933, loss: 0.034513, Train_acc: 0.984375 Epoch:4, train_step: 3934, loss: 0.007226, Train_acc: 1.000000 Epoch:4, train_step: 3935, loss: 0.003638, Train_acc: 1.000000 Epoch:4, train_step: 3936, loss: 0.006999, Train_acc: 1.000000 Epoch:4, train_step: 3937, loss: 0.002325, Train_acc: 1.000000 Epoch:4, train_step: 3938, loss: 0.005230, Train_acc: 1.000000 Epoch:4, train_step: 3939, loss: 0.021520, Train_acc: 0.984375 Epoch:4, train_step: 3940, loss: 0.068464, Train_acc: 0.968750 Epoch:4, train_step: 3941, loss: 0.002874, Train_acc: 1.000000 Epoch:4, train_step: 3942, loss: 0.010548, Train_acc: 1.000000 Epoch:4, train_step: 3943, loss: 0.003110, Train_acc: 1.000000 Epoch:4, train_step: 3944, loss: 0.000177, Train_acc: 1.000000 Epoch:4, train_step: 3945, loss: 0.061661, Train_acc: 0.984375 Epoch:4, train_step: 3946, loss: 0.013240, Train_acc: 1.000000 Epoch:4, train_step: 3947, loss: 0.000211, Train_acc: 1.000000 Epoch:4, train_step: 3948, loss: 0.008291, Train_acc: 1.000000 Epoch:4, train_step: 3949, loss: 0.003167, Train_acc: 1.000000 Epoch:4, train_step: 3950, loss: 0.007857, Train_acc: 1.000000 Epoch:4, train_step: 3951, loss: 0.028541, Train_acc: 0.984375 Epoch:4, train_step: 3952, loss: 0.004121, Train_acc: 1.000000 Epoch:4, train_step: 3953, loss: 0.014246, Train_acc: 1.000000 Epoch:4, train_step: 3954, loss: 0.002328, Train_acc: 1.000000 Epoch:4, train_step: 3955, loss: 0.001072, Train_acc: 1.000000 Epoch:4, train_step: 3956, loss: 0.001048, Train_acc: 1.000000 Epoch:4, train_step: 3957, loss: 0.005467, Train_acc: 1.000000 Epoch:4, train_step: 3958, loss: 0.028630, Train_acc: 0.984375 Epoch:4, train_step: 3959, loss: 0.007064, Train_acc: 1.000000 Epoch:4, train_step: 3960, loss: 0.002030, Train_acc: 1.000000 Epoch:4, train_step: 3961, loss: 0.005823, Train_acc: 1.000000 Epoch:4, train_step: 3962, loss: 0.013369, Train_acc: 1.000000 Epoch:4, train_step: 3963, loss: 0.012357, Train_acc: 1.000000 Epoch:4, train_step: 3964, loss: 0.000665, Train_acc: 1.000000 Epoch:4, train_step: 3965, loss: 0.014200, Train_acc: 0.984375 Epoch:4, train_step: 3966, loss: 0.003094, Train_acc: 1.000000 Epoch:4, train_step: 3967, loss: 0.025154, Train_acc: 1.000000 Epoch:4, train_step: 3968, loss: 0.012021, Train_acc: 0.984375 Epoch:4, train_step: 3969, loss: 0.005900, Train_acc: 1.000000 Epoch:4, train_step: 3970, loss: 0.002634, Train_acc: 1.000000 Epoch:4, train_step: 3971, loss: 0.007482, Train_acc: 1.000000 Epoch:4, train_step: 3972, loss: 0.012384, Train_acc: 1.000000 Epoch:4, train_step: 3973, loss: 0.014254, Train_acc: 0.984375 Epoch:4, train_step: 3974, loss: 0.007183, Train_acc: 1.000000 Epoch:4, train_step: 3975, loss: 0.002026, Train_acc: 1.000000 Epoch:4, train_step: 3976, loss: 0.042307, Train_acc: 0.984375 Epoch:4, train_step: 3977, loss: 0.000782, Train_acc: 1.000000 Epoch:4, train_step: 3978, loss: 0.010536, Train_acc: 1.000000 Epoch:4, train_step: 3979, loss: 0.015805, Train_acc: 0.984375 Epoch:4, train_step: 3980, loss: 0.026071, Train_acc: 0.984375 Epoch:4, train_step: 3981, loss: 0.000530, Train_acc: 1.000000 Epoch:4, train_step: 3982, loss: 0.006114, Train_acc: 1.000000 Epoch:4, train_step: 3983, loss: 0.000987, Train_acc: 1.000000 Epoch:4, train_step: 3984, loss: 0.013415, Train_acc: 0.984375 Epoch:4, train_step: 3985, loss: 0.011494, Train_acc: 1.000000 Epoch:4, train_step: 3986, loss: 0.010015, Train_acc: 1.000000 Epoch:4, train_step: 3987, loss: 0.001366, Train_acc: 1.000000 Epoch:4, train_step: 3988, loss: 0.025998, Train_acc: 0.984375 Epoch:4, train_step: 3989, loss: 0.001559, Train_acc: 1.000000 Epoch:4, train_step: 3990, loss: 0.004993, Train_acc: 1.000000 Epoch:4, train_step: 3991, loss: 0.001165, Train_acc: 1.000000 Epoch:4, train_step: 3992, loss: 0.001414, Train_acc: 1.000000 Epoch:4, train_step: 3993, loss: 0.006102, Train_acc: 1.000000 Epoch:4, train_step: 3994, loss: 0.001435, Train_acc: 1.000000 Epoch:4, train_step: 3995, loss: 0.007573, Train_acc: 1.000000 Epoch:4, train_step: 3996, loss: 0.001160, Train_acc: 1.000000 Epoch:4, train_step: 3997, loss: 0.004560, Train_acc: 1.000000 Epoch:4, train_step: 3998, loss: 0.033815, Train_acc: 0.984375 Epoch:4, train_step: 3999, loss: 0.005957, Train_acc: 1.000000 Epoch:4, train_step: 4000, loss: 0.008179, Train_acc: 1.000000 Epoch:4, train_step: 4001, loss: 0.014600, Train_acc: 1.000000 Epoch:4, train_step: 4002, loss: 0.000684, Train_acc: 1.000000 Epoch:4, train_step: 4003, loss: 0.008651, Train_acc: 1.000000 Epoch:4, train_step: 4004, loss: 0.004218, Train_acc: 1.000000 Epoch:4, train_step: 4005, loss: 0.005039, Train_acc: 1.000000 Epoch:4, train_step: 4006, loss: 0.000788, Train_acc: 1.000000 Epoch:4, train_step: 4007, loss: 0.004645, Train_acc: 1.000000 Epoch:4, train_step: 4008, loss: 0.000283, Train_acc: 1.000000 Epoch:4, train_step: 4009, loss: 0.052247, Train_acc: 0.968750 Epoch:4, train_step: 4010, loss: 0.020683, Train_acc: 0.984375 Epoch:4, train_step: 4011, loss: 0.001021, Train_acc: 1.000000 Epoch:4, train_step: 4012, loss: 0.009951, Train_acc: 1.000000 Epoch:4, train_step: 4013, loss: 0.044322, Train_acc: 0.984375 Epoch:4, train_step: 4014, loss: 0.004332, Train_acc: 1.000000 Epoch:4, train_step: 4015, loss: 0.005396, Train_acc: 1.000000 Epoch:4, train_step: 4016, loss: 0.005489, Train_acc: 1.000000 Epoch:4, train_step: 4017, loss: 0.015937, Train_acc: 1.000000 Epoch:4, train_step: 4018, loss: 0.010195, Train_acc: 1.000000 Epoch:4, train_step: 4019, loss: 0.000515, Train_acc: 1.000000 Epoch:4, train_step: 4020, loss: 0.002930, Train_acc: 1.000000 Epoch:4, train_step: 4021, loss: 0.013084, Train_acc: 0.984375 Epoch:4, train_step: 4022, loss: 0.010307, Train_acc: 1.000000 Epoch:4, train_step: 4023, loss: 0.048714, Train_acc: 0.984375 Epoch:4, train_step: 4024, loss: 0.016293, Train_acc: 0.984375 Epoch:4, train_step: 4025, loss: 0.018047, Train_acc: 0.984375 Epoch:4, train_step: 4026, loss: 0.013627, Train_acc: 0.984375 Epoch:4, train_step: 4027, loss: 0.033546, Train_acc: 0.968750 Epoch:4, train_step: 4028, loss: 0.003611, Train_acc: 1.000000 Epoch:4, train_step: 4029, loss: 0.022289, Train_acc: 0.984375 Epoch:4, train_step: 4030, loss: 0.002280, Train_acc: 1.000000 Epoch:4, train_step: 4031, loss: 0.010048, Train_acc: 1.000000 Epoch:4, train_step: 4032, loss: 0.009790, Train_acc: 1.000000 Epoch:4, train_step: 4033, loss: 0.006704, Train_acc: 1.000000 Epoch:4, train_step: 4034, loss: 0.003132, Train_acc: 1.000000 Epoch:4, train_step: 4035, loss: 0.004535, Train_acc: 1.000000 Epoch:4, train_step: 4036, loss: 0.055699, Train_acc: 0.953125 Epoch:4, train_step: 4037, loss: 0.002061, Train_acc: 1.000000 Epoch:4, train_step: 4038, loss: 0.010016, Train_acc: 1.000000 Epoch:4, train_step: 4039, loss: 0.001599, Train_acc: 1.000000 Epoch:4, train_step: 4040, loss: 0.033800, Train_acc: 0.984375 Epoch:4, train_step: 4041, loss: 0.015528, Train_acc: 1.000000 Epoch:4, train_step: 4042, loss: 0.001337, Train_acc: 1.000000 Epoch:4, train_step: 4043, loss: 0.009485, Train_acc: 1.000000 Epoch:4, train_step: 4044, loss: 0.000586, Train_acc: 1.000000 Epoch:4, train_step: 4045, loss: 0.001238, Train_acc: 1.000000 Epoch:4, train_step: 4046, loss: 0.010290, Train_acc: 1.000000 Epoch:4, train_step: 4047, loss: 0.011783, Train_acc: 1.000000 Epoch:4, train_step: 4048, loss: 0.013395, Train_acc: 1.000000 Epoch:4, train_step: 4049, loss: 0.007580, Train_acc: 1.000000 Epoch:4, train_step: 4050, loss: 0.002758, Train_acc: 1.000000 Epoch:4, train_step: 4051, loss: 0.047611, Train_acc: 0.984375 Epoch:4, train_step: 4052, loss: 0.001492, Train_acc: 1.000000 Epoch:4, train_step: 4053, loss: 0.008314, Train_acc: 1.000000 Epoch:4, train_step: 4054, loss: 0.014635, Train_acc: 1.000000 Epoch:4, train_step: 4055, loss: 0.012389, Train_acc: 1.000000 Epoch:4, train_step: 4056, loss: 0.000563, Train_acc: 1.000000 Epoch:4, train_step: 4057, loss: 0.001692, Train_acc: 1.000000 Epoch:4, train_step: 4058, loss: 0.026722, Train_acc: 0.984375 Epoch:4, train_step: 4059, loss: 0.009762, Train_acc: 1.000000 Epoch:4, train_step: 4060, loss: 0.009400, Train_acc: 1.000000 Epoch:4, train_step: 4061, loss: 0.001684, Train_acc: 1.000000 Epoch:4, train_step: 4062, loss: 0.016372, Train_acc: 1.000000 Epoch:4, train_step: 4063, loss: 0.047342, Train_acc: 0.984375 Epoch:4, train_step: 4064, loss: 0.015327, Train_acc: 1.000000 Epoch:4, train_step: 4065, loss: 0.017483, Train_acc: 1.000000 Epoch:4, train_step: 4066, loss: 0.002267, Train_acc: 1.000000 Epoch:4, train_step: 4067, loss: 0.004719, Train_acc: 1.000000 Epoch:4, train_step: 4068, loss: 0.003370, Train_acc: 1.000000 Epoch:4, train_step: 4069, loss: 0.006854, Train_acc: 1.000000 Epoch:4, train_step: 4070, loss: 0.002931, Train_acc: 1.000000 Epoch:4, train_step: 4071, loss: 0.019215, Train_acc: 1.000000 Epoch:4, train_step: 4072, loss: 0.010261, Train_acc: 1.000000 Epoch:4, train_step: 4073, loss: 0.037648, Train_acc: 0.984375 Epoch:4, train_step: 4074, loss: 0.008536, Train_acc: 1.000000 Epoch:4, train_step: 4075, loss: 0.001810, Train_acc: 1.000000 Epoch:4, train_step: 4076, loss: 0.001317, Train_acc: 1.000000 Epoch:4, train_step: 4077, loss: 0.004220, Train_acc: 1.000000 Epoch:4, train_step: 4078, loss: 0.000348, Train_acc: 1.000000 Epoch:4, train_step: 4079, loss: 0.008714, Train_acc: 1.000000 Epoch:4, train_step: 4080, loss: 0.000505, Train_acc: 1.000000 Epoch:4, train_step: 4081, loss: 0.013718, Train_acc: 0.984375 Epoch:4, train_step: 4082, loss: 0.014356, Train_acc: 1.000000 Epoch:4, train_step: 4083, loss: 0.001928, Train_acc: 1.000000 Epoch:4, train_step: 4084, loss: 0.004003, Train_acc: 1.000000 Epoch:4, train_step: 4085, loss: 0.000967, Train_acc: 1.000000 Epoch:4, train_step: 4086, loss: 0.004098, Train_acc: 1.000000 Epoch:4, train_step: 4087, loss: 0.012725, Train_acc: 1.000000 Epoch:4, train_step: 4088, loss: 0.010908, Train_acc: 1.000000 Epoch:4, train_step: 4089, loss: 0.013139, Train_acc: 0.984375 Epoch:4, train_step: 4090, loss: 0.003673, Train_acc: 1.000000 Epoch:4, train_step: 4091, loss: 0.039176, Train_acc: 0.984375 Epoch:4, train_step: 4092, loss: 0.034208, Train_acc: 0.984375 Epoch:4, train_step: 4093, loss: 0.002383, Train_acc: 1.000000 Epoch:4, train_step: 4094, loss: 0.011858, Train_acc: 1.000000 Epoch:4, train_step: 4095, loss: 0.008179, Train_acc: 1.000000 Epoch:4, train_step: 4096, loss: 0.002288, Train_acc: 1.000000 Epoch:4, train_step: 4097, loss: 0.006435, Train_acc: 1.000000 Epoch:4, train_step: 4098, loss: 0.004362, Train_acc: 1.000000 Epoch:4, train_step: 4099, loss: 0.009567, Train_acc: 1.000000 Epoch:4, train_step: 4100, loss: 0.007727, Train_acc: 1.000000 Epoch:4, train_step: 4101, loss: 0.013206, Train_acc: 1.000000 Epoch:4, train_step: 4102, loss: 0.019548, Train_acc: 1.000000 Epoch:4, train_step: 4103, loss: 0.006046, Train_acc: 1.000000 Epoch:4, train_step: 4104, loss: 0.003030, Train_acc: 1.000000 Epoch:4, train_step: 4105, loss: 0.003514, Train_acc: 1.000000 Epoch:4, train_step: 4106, loss: 0.003125, Train_acc: 1.000000 Epoch:4, train_step: 4107, loss: 0.000645, Train_acc: 1.000000 Epoch:4, train_step: 4108, loss: 0.005009, Train_acc: 1.000000 Epoch:4, train_step: 4109, loss: 0.006563, Train_acc: 1.000000 Epoch:4, train_step: 4110, loss: 0.005172, Train_acc: 1.000000 Epoch:4, train_step: 4111, loss: 0.006128, Train_acc: 1.000000 Epoch:4, train_step: 4112, loss: 0.003891, Train_acc: 1.000000 Epoch:4, train_step: 4113, loss: 0.000407, Train_acc: 1.000000 Epoch:4, train_step: 4114, loss: 0.005651, Train_acc: 1.000000 Epoch:4, train_step: 4115, loss: 0.016604, Train_acc: 0.984375 Epoch:4, train_step: 4116, loss: 0.002237, Train_acc: 1.000000 Epoch:4, train_step: 4117, loss: 0.038894, Train_acc: 0.984375 Epoch:4, train_step: 4118, loss: 0.005075, Train_acc: 1.000000 Epoch:4, train_step: 4119, loss: 0.006575, Train_acc: 1.000000 Epoch:4, train_step: 4120, loss: 0.005806, Train_acc: 1.000000 Epoch:4, train_step: 4121, loss: 0.027676, Train_acc: 0.984375 Epoch:4, train_step: 4122, loss: 0.110841, Train_acc: 0.984375 Epoch:4, train_step: 4123, loss: 0.009261, Train_acc: 1.000000 Epoch:4, train_step: 4124, loss: 0.012755, Train_acc: 0.984375 Epoch:4, train_step: 4125, loss: 0.007757, Train_acc: 1.000000 Epoch:4, train_step: 4126, loss: 0.007338, Train_acc: 1.000000 Epoch:4, train_step: 4127, loss: 0.003745, Train_acc: 1.000000 Epoch:4, train_step: 4128, loss: 0.012167, Train_acc: 1.000000 Epoch:4, train_step: 4129, loss: 0.000392, Train_acc: 1.000000 Epoch:4, train_step: 4130, loss: 0.006967, Train_acc: 1.000000 Epoch:4, train_step: 4131, loss: 0.004295, Train_acc: 1.000000 Epoch:4, train_step: 4132, loss: 0.013046, Train_acc: 1.000000 Epoch:4, train_step: 4133, loss: 0.012872, Train_acc: 1.000000 Epoch:4, train_step: 4134, loss: 0.004171, Train_acc: 1.000000 Epoch:4, train_step: 4135, loss: 0.002714, Train_acc: 1.000000 Epoch:4, train_step: 4136, loss: 0.002808, Train_acc: 1.000000 Epoch:4, train_step: 4137, loss: 0.007440, Train_acc: 1.000000 Epoch:4, train_step: 4138, loss: 0.003920, Train_acc: 1.000000 Epoch:4, train_step: 4139, loss: 0.000341, Train_acc: 1.000000 Epoch:4, train_step: 4140, loss: 0.016620, Train_acc: 0.984375 Epoch:4, train_step: 4141, loss: 0.003272, Train_acc: 1.000000 Epoch:4, train_step: 4142, loss: 0.003964, Train_acc: 1.000000 Epoch:4, train_step: 4143, loss: 0.009142, Train_acc: 1.000000 Epoch:4, train_step: 4144, loss: 0.002388, Train_acc: 1.000000 Epoch:4, train_step: 4145, loss: 0.000238, Train_acc: 1.000000 Epoch:4, train_step: 4146, loss: 0.000337, Train_acc: 1.000000 Epoch:4, train_step: 4147, loss: 0.003451, Train_acc: 1.000000 Epoch:4, train_step: 4148, loss: 0.013765, Train_acc: 1.000000 Epoch:4, train_step: 4149, loss: 0.002607, Train_acc: 1.000000 Epoch:4, train_step: 4150, loss: 0.050324, Train_acc: 0.984375 Epoch:4, train_step: 4151, loss: 0.005250, Train_acc: 1.000000 Epoch:4, train_step: 4152, loss: 0.004567, Train_acc: 1.000000 Epoch:4, train_step: 4153, loss: 0.010646, Train_acc: 1.000000 Epoch:4, train_step: 4154, loss: 0.003627, Train_acc: 1.000000 Epoch:4, train_step: 4155, loss: 0.040271, Train_acc: 0.984375 Epoch:4, train_step: 4156, loss: 0.003023, Train_acc: 1.000000 Epoch:4, train_step: 4157, loss: 0.002175, Train_acc: 1.000000 Epoch:4, train_step: 4158, loss: 0.083437, Train_acc: 0.984375 Epoch:4, train_step: 4159, loss: 0.010653, Train_acc: 1.000000 Epoch:4, train_step: 4160, loss: 0.014912, Train_acc: 0.984375 Epoch:4, train_step: 4161, loss: 0.033890, Train_acc: 0.984375 Epoch:4, train_step: 4162, loss: 0.024321, Train_acc: 0.984375 Epoch:4, train_step: 4163, loss: 0.055164, Train_acc: 0.968750 Epoch:4, train_step: 4164, loss: 0.106909, Train_acc: 0.968750 Epoch:4, train_step: 4165, loss: 0.118369, Train_acc: 0.968750 Epoch:4, train_step: 4166, loss: 0.033023, Train_acc: 0.968750 Epoch:4, train_step: 4167, loss: 0.003654, Train_acc: 1.000000 Epoch:4, train_step: 4168, loss: 0.038640, Train_acc: 0.984375 Epoch:4, train_step: 4169, loss: 0.056377, Train_acc: 0.968750 Epoch:4, train_step: 4170, loss: 0.001232, Train_acc: 1.000000 Epoch:4, train_step: 4171, loss: 0.002143, Train_acc: 1.000000 Epoch:4, train_step: 4172, loss: 0.025085, Train_acc: 0.984375 Epoch:4, train_step: 4173, loss: 0.004084, Train_acc: 1.000000 Epoch:4, train_step: 4174, loss: 0.015428, Train_acc: 1.000000 Epoch:4, train_step: 4175, loss: 0.003326, Train_acc: 1.000000 Epoch:4, train_step: 4176, loss: 0.003326, Train_acc: 1.000000 Epoch:4, train_step: 4177, loss: 0.010731, Train_acc: 1.000000 Epoch:4, train_step: 4178, loss: 0.034811, Train_acc: 0.968750 Epoch:4, train_step: 4179, loss: 0.001242, Train_acc: 1.000000 Epoch:4, train_step: 4180, loss: 0.004752, Train_acc: 1.000000 Epoch:4, train_step: 4181, loss: 0.007382, Train_acc: 1.000000 Epoch:4, train_step: 4182, loss: 0.006139, Train_acc: 1.000000 Epoch:4, train_step: 4183, loss: 0.003776, Train_acc: 1.000000 Epoch:4, train_step: 4184, loss: 0.094060, Train_acc: 0.984375 Epoch:4, train_step: 4185, loss: 0.001184, Train_acc: 1.000000 Epoch:4, train_step: 4186, loss: 0.029294, Train_acc: 0.984375 Epoch:4, train_step: 4187, loss: 0.000142, Train_acc: 1.000000 Epoch:4, train_step: 4188, loss: 0.003747, Train_acc: 1.000000 Epoch:4, train_step: 4189, loss: 0.002650, Train_acc: 1.000000 Epoch:4, train_step: 4190, loss: 0.029085, Train_acc: 0.984375 Epoch:4, train_step: 4191, loss: 0.002638, Train_acc: 1.000000 Epoch:4, train_step: 4192, loss: 0.056354, Train_acc: 0.984375 Epoch:4, train_step: 4193, loss: 0.008371, Train_acc: 1.000000 Epoch:4, train_step: 4194, loss: 0.004032, Train_acc: 1.000000 Epoch:4, train_step: 4195, loss: 0.001278, Train_acc: 1.000000 Epoch:4, train_step: 4196, loss: 0.071611, Train_acc: 0.968750 Epoch:4, train_step: 4197, loss: 0.113404, Train_acc: 0.968750 Epoch:4, train_step: 4198, loss: 0.002530, Train_acc: 1.000000 Epoch:4, train_step: 4199, loss: 0.003210, Train_acc: 1.000000 Epoch:4, train_step: 4200, loss: 0.003929, Train_acc: 1.000000 Epoch:4, train_step: 4201, loss: 0.006078, Train_acc: 1.000000 Epoch:4, train_step: 4202, loss: 0.024657, Train_acc: 0.984375 Epoch:4, train_step: 4203, loss: 0.004519, Train_acc: 1.000000 Epoch:4, train_step: 4204, loss: 0.016370, Train_acc: 1.000000 Epoch:4, train_step: 4205, loss: 0.009613, Train_acc: 1.000000 Epoch:4, train_step: 4206, loss: 0.011758, Train_acc: 1.000000 Epoch:4, train_step: 4207, loss: 0.018404, Train_acc: 0.984375 Epoch:4, train_step: 4208, loss: 0.000566, Train_acc: 1.000000 Epoch:4, train_step: 4209, loss: 0.010097, Train_acc: 1.000000 Epoch:4, train_step: 4210, loss: 0.000628, Train_acc: 1.000000 Epoch:4, train_step: 4211, loss: 0.008510, Train_acc: 1.000000 Epoch:4, train_step: 4212, loss: 0.001616, Train_acc: 1.000000 Epoch:4, train_step: 4213, loss: 0.016007, Train_acc: 1.000000 Epoch:4, train_step: 4214, loss: 0.002449, Train_acc: 1.000000 Epoch:4, train_step: 4215, loss: 0.002807, Train_acc: 1.000000 Epoch:4, train_step: 4216, loss: 0.005939, Train_acc: 1.000000 Epoch:4, train_step: 4217, loss: 0.001883, Train_acc: 1.000000 Epoch:4, train_step: 4218, loss: 0.006955, Train_acc: 1.000000 Epoch:4, train_step: 4219, loss: 0.002795, Train_acc: 1.000000 Epoch:4, train_step: 4220, loss: 0.009915, Train_acc: 1.000000 Epoch:4, train_step: 4221, loss: 0.003899, Train_acc: 1.000000 Epoch:4, train_step: 4222, loss: 0.001851, Train_acc: 1.000000 Epoch:4, train_step: 4223, loss: 0.000534, Train_acc: 1.000000 Epoch:4, train_step: 4224, loss: 0.001035, Train_acc: 1.000000 Epoch:4, train_step: 4225, loss: 0.012403, Train_acc: 1.000000 Epoch:4, train_step: 4226, loss: 0.000631, Train_acc: 1.000000 Epoch:4, train_step: 4227, loss: 0.006207, Train_acc: 1.000000 Epoch:4, train_step: 4228, loss: 0.011873, Train_acc: 1.000000 Epoch:4, train_step: 4229, loss: 0.012308, Train_acc: 0.984375 Epoch:4, train_step: 4230, loss: 0.019241, Train_acc: 0.984375 Epoch:4, train_step: 4231, loss: 0.004751, Train_acc: 1.000000 Epoch:4, train_step: 4232, loss: 0.006658, Train_acc: 1.000000 Epoch:4, train_step: 4233, loss: 0.000353, Train_acc: 1.000000 Epoch:4, train_step: 4234, loss: 0.005619, Train_acc: 1.000000 Epoch:4, train_step: 4235, loss: 0.013665, Train_acc: 0.984375 Epoch:4, train_step: 4236, loss: 0.013088, Train_acc: 0.984375 Epoch:4, train_step: 4237, loss: 0.024113, Train_acc: 0.984375 Epoch:4, train_step: 4238, loss: 0.001828, Train_acc: 1.000000 Epoch:4, train_step: 4239, loss: 0.003507, Train_acc: 1.000000 Epoch:4, train_step: 4240, loss: 0.015485, Train_acc: 0.984375 Epoch:4, train_step: 4241, loss: 0.069928, Train_acc: 0.953125 Epoch:4, train_step: 4242, loss: 0.050417, Train_acc: 0.984375 Epoch:4, train_step: 4243, loss: 0.007495, Train_acc: 1.000000 Epoch:4, train_step: 4244, loss: 0.006356, Train_acc: 1.000000 Epoch:4, train_step: 4245, loss: 0.006741, Train_acc: 1.000000 Epoch:4, train_step: 4246, loss: 0.021586, Train_acc: 0.984375 Epoch:4, train_step: 4247, loss: 0.002145, Train_acc: 1.000000 Epoch:4, train_step: 4248, loss: 0.003297, Train_acc: 1.000000 Epoch:4, train_step: 4249, loss: 0.001281, Train_acc: 1.000000 Epoch:4, train_step: 4250, loss: 0.053092, Train_acc: 0.968750 Epoch:4, train_step: 4251, loss: 0.010927, Train_acc: 1.000000 Epoch:4, train_step: 4252, loss: 0.006173, Train_acc: 1.000000 Epoch:4, train_step: 4253, loss: 0.001591, Train_acc: 1.000000 Epoch:4, train_step: 4254, loss: 0.161263, Train_acc: 0.968750 Epoch:4, train_step: 4255, loss: 0.010028, Train_acc: 1.000000 Epoch:4, train_step: 4256, loss: 0.022667, Train_acc: 0.984375 Epoch:4, train_step: 4257, loss: 0.012477, Train_acc: 1.000000 Epoch:4, train_step: 4258, loss: 0.002092, Train_acc: 1.000000 Epoch:4, train_step: 4259, loss: 0.087891, Train_acc: 0.968750 Epoch:4, train_step: 4260, loss: 0.003634, Train_acc: 1.000000 Epoch:4, train_step: 4261, loss: 0.012711, Train_acc: 1.000000 Epoch:4, train_step: 4262, loss: 0.011951, Train_acc: 1.000000 Epoch:4, train_step: 4263, loss: 0.006702, Train_acc: 1.000000 Epoch:4, train_step: 4264, loss: 0.000297, Train_acc: 1.000000 Epoch:4, train_step: 4265, loss: 0.019186, Train_acc: 0.984375 Epoch:4, train_step: 4266, loss: 0.007270, Train_acc: 1.000000 Epoch:4, train_step: 4267, loss: 0.002577, Train_acc: 1.000000 Epoch:4, train_step: 4268, loss: 0.016128, Train_acc: 0.984375 Epoch:4, train_step: 4269, loss: 0.025551, Train_acc: 0.984375 Epoch:4, train_step: 4270, loss: 0.001921, Train_acc: 1.000000 Epoch:4, train_step: 4271, loss: 0.028973, Train_acc: 0.984375 Epoch:4, train_step: 4272, loss: 0.014975, Train_acc: 0.984375 Epoch:4, train_step: 4273, loss: 0.042976, Train_acc: 0.984375 Epoch:4, train_step: 4274, loss: 0.028085, Train_acc: 0.984375 Epoch:4, train_step: 4275, loss: 0.003300, Train_acc: 1.000000 Epoch:4, train_step: 4276, loss: 0.105803, Train_acc: 0.984375 Epoch:4, train_step: 4277, loss: 0.001081, Train_acc: 1.000000 Epoch:4, train_step: 4278, loss: 0.001049, Train_acc: 1.000000 Epoch:4, train_step: 4279, loss: 0.000668, Train_acc: 1.000000 Epoch:4, train_step: 4280, loss: 0.000879, Train_acc: 1.000000 Epoch:4, train_step: 4281, loss: 0.000564, Train_acc: 1.000000 Epoch:4, train_step: 4282, loss: 0.001628, Train_acc: 1.000000 Epoch:4, train_step: 4283, loss: 0.000583, Train_acc: 1.000000 Epoch:4, train_step: 4284, loss: 0.000433, Train_acc: 1.000000 Epoch:4, train_step: 4285, loss: 0.011534, Train_acc: 1.000000 Epoch:4, train_step: 4286, loss: 0.012451, Train_acc: 1.000000 Epoch:4, train_step: 4287, loss: 0.030715, Train_acc: 0.984375 Epoch:4, train_step: 4288, loss: 0.024785, Train_acc: 0.984375 Epoch:4, train_step: 4289, loss: 0.001980, Train_acc: 1.000000 Epoch:4, train_step: 4290, loss: 0.062979, Train_acc: 0.968750 Epoch:4, train_step: 4291, loss: 0.048190, Train_acc: 0.984375 Epoch:4, train_step: 4292, loss: 0.000638, Train_acc: 1.000000 Epoch:4, train_step: 4293, loss: 0.031832, Train_acc: 0.984375 Epoch:4, train_step: 4294, loss: 0.059847, Train_acc: 0.984375 Epoch:4, train_step: 4295, loss: 0.004988, Train_acc: 1.000000 Epoch:4, train_step: 4296, loss: 0.033478, Train_acc: 0.984375 Epoch:4, train_step: 4297, loss: 0.002320, Train_acc: 1.000000 Epoch:4, train_step: 4298, loss: 0.079357, Train_acc: 0.968750 Epoch:4, train_step: 4299, loss: 0.050480, Train_acc: 0.968750 Epoch:4, train_step: 4300, loss: 0.023487, Train_acc: 0.984375 Epoch:4, train_step: 4301, loss: 0.020239, Train_acc: 1.000000 Epoch:4, train_step: 4302, loss: 0.001429, Train_acc: 1.000000 Epoch:4, train_step: 4303, loss: 0.083324, Train_acc: 0.968750 Epoch:4, train_step: 4304, loss: 0.005585, Train_acc: 1.000000 Epoch:4, train_step: 4305, loss: 0.085215, Train_acc: 0.984375 Epoch:4, train_step: 4306, loss: 0.003325, Train_acc: 1.000000 Epoch:4, train_step: 4307, loss: 0.011528, Train_acc: 1.000000 Epoch:4, train_step: 4308, loss: 0.000714, Train_acc: 1.000000 Epoch:4, train_step: 4309, loss: 0.022184, Train_acc: 0.984375 Epoch:4, train_step: 4310, loss: 0.036429, Train_acc: 0.984375 Epoch:4, train_step: 4311, loss: 0.024768, Train_acc: 0.984375 Epoch:4, train_step: 4312, loss: 0.001617, Train_acc: 1.000000 Epoch:4, train_step: 4313, loss: 0.033062, Train_acc: 0.984375 Epoch:4, train_step: 4314, loss: 0.023679, Train_acc: 0.984375 Epoch:4, train_step: 4315, loss: 0.002283, Train_acc: 1.000000 Epoch:4, train_step: 4316, loss: 0.000499, Train_acc: 1.000000 Epoch:4, train_step: 4317, loss: 0.005818, Train_acc: 1.000000 Epoch:4, train_step: 4318, loss: 0.002865, Train_acc: 1.000000 Epoch:4, train_step: 4319, loss: 0.003020, Train_acc: 1.000000 Epoch:4, train_step: 4320, loss: 0.001367, Train_acc: 1.000000 Epoch:4, train_step: 4321, loss: 0.018854, Train_acc: 1.000000 Epoch:4, train_step: 4322, loss: 0.067725, Train_acc: 0.968750 Epoch:4, train_step: 4323, loss: 0.028950, Train_acc: 0.984375 Epoch:4, train_step: 4324, loss: 0.103260, Train_acc: 0.984375 Epoch:4, train_step: 4325, loss: 0.001543, Train_acc: 1.000000 Epoch:4, train_step: 4326, loss: 0.017744, Train_acc: 0.984375 Epoch:4, train_step: 4327, loss: 0.103983, Train_acc: 0.984375 Epoch:4, train_step: 4328, loss: 0.012242, Train_acc: 1.000000 Epoch:4, train_step: 4329, loss: 0.012380, Train_acc: 1.000000 Epoch:4, train_step: 4330, loss: 0.001642, Train_acc: 1.000000 Epoch:4, train_step: 4331, loss: 0.000604, Train_acc: 1.000000 Epoch:4, train_step: 4332, loss: 0.013899, Train_acc: 0.984375 Epoch:4, train_step: 4333, loss: 0.040071, Train_acc: 0.984375 Epoch:4, train_step: 4334, loss: 0.013294, Train_acc: 1.000000 Epoch:4, train_step: 4335, loss: 0.002083, Train_acc: 1.000000 Epoch:4, train_step: 4336, loss: 0.003270, Train_acc: 1.000000 Epoch:4, train_step: 4337, loss: 0.040400, Train_acc: 0.984375 Epoch:4, train_step: 4338, loss: 0.017618, Train_acc: 0.984375 Epoch:4, train_step: 4339, loss: 0.004352, Train_acc: 1.000000 Epoch:4, train_step: 4340, loss: 0.048746, Train_acc: 0.968750 Epoch:4, train_step: 4341, loss: 0.002944, Train_acc: 1.000000 Epoch:4, train_step: 4342, loss: 0.008438, Train_acc: 1.000000 Epoch:4, train_step: 4343, loss: 0.001479, Train_acc: 1.000000 Epoch:4, train_step: 4344, loss: 0.003264, Train_acc: 1.000000 Epoch:4, train_step: 4345, loss: 0.001164, Train_acc: 1.000000 Epoch:4, train_step: 4346, loss: 0.041931, Train_acc: 0.984375 Epoch:4, train_step: 4347, loss: 0.002748, Train_acc: 1.000000 Epoch:4, train_step: 4348, loss: 0.053714, Train_acc: 0.984375 Epoch:4, train_step: 4349, loss: 0.043587, Train_acc: 0.984375 Epoch:4, train_step: 4350, loss: 0.030108, Train_acc: 0.984375 Epoch:4, train_step: 4351, loss: 0.011086, Train_acc: 1.000000 Epoch:4, train_step: 4352, loss: 0.015788, Train_acc: 1.000000 Epoch:4, train_step: 4353, loss: 0.108052, Train_acc: 0.984375 Epoch:4, train_step: 4354, loss: 0.015388, Train_acc: 0.984375 Epoch:4, train_step: 4355, loss: 0.000729, Train_acc: 1.000000 Epoch:4, train_step: 4356, loss: 0.014495, Train_acc: 1.000000 Epoch:4, train_step: 4357, loss: 0.000652, Train_acc: 1.000000 Epoch:4, train_step: 4358, loss: 0.025755, Train_acc: 0.984375 Epoch:4, train_step: 4359, loss: 0.000930, Train_acc: 1.000000 Epoch:4, train_step: 4360, loss: 0.001099, Train_acc: 1.000000 Epoch:4, train_step: 4361, loss: 0.007948, Train_acc: 1.000000 Epoch:4, train_step: 4362, loss: 0.012085, Train_acc: 1.000000 Epoch:4, train_step: 4363, loss: 0.060608, Train_acc: 0.984375 Epoch:4, train_step: 4364, loss: 0.045394, Train_acc: 0.968750 Epoch:4, train_step: 4365, loss: 0.013072, Train_acc: 1.000000 Epoch:4, train_step: 4366, loss: 0.001615, Train_acc: 1.000000 Epoch:4, train_step: 4367, loss: 0.003516, Train_acc: 1.000000 Epoch:4, train_step: 4368, loss: 0.013819, Train_acc: 1.000000 Epoch:4, train_step: 4369, loss: 0.061648, Train_acc: 0.984375 Epoch:4, train_step: 4370, loss: 0.032362, Train_acc: 0.984375 Epoch:4, train_step: 4371, loss: 0.018747, Train_acc: 1.000000 Epoch:4, train_step: 4372, loss: 0.002279, Train_acc: 1.000000 Epoch:4, train_step: 4373, loss: 0.006018, Train_acc: 1.000000 Epoch:4, train_step: 4374, loss: 0.021804, Train_acc: 0.984375 Epoch:4, train_step: 4375, loss: 0.021441, Train_acc: 0.984375 Epoch:4, train_step: 4376, loss: 0.137516, Train_acc: 0.984375 Epoch:4, train_step: 4377, loss: 0.015502, Train_acc: 1.000000 Epoch:4, train_step: 4378, loss: 0.022087, Train_acc: 1.000000 Epoch:4, train_step: 4379, loss: 0.029597, Train_acc: 0.984375 Epoch:4, train_step: 4380, loss: 0.041901, Train_acc: 0.984375 Epoch:4, train_step: 4381, loss: 0.000911, Train_acc: 1.000000 Epoch:4, train_step: 4382, loss: 0.003479, Train_acc: 1.000000 Epoch:4, train_step: 4383, loss: 0.011190, Train_acc: 1.000000 Epoch:4, train_step: 4384, loss: 0.002416, Train_acc: 1.000000 Epoch:4, train_step: 4385, loss: 0.003130, Train_acc: 1.000000 Epoch:4, train_step: 4386, loss: 0.002756, Train_acc: 1.000000 Epoch:4, train_step: 4387, loss: 0.038618, Train_acc: 0.984375 Epoch:4, train_step: 4388, loss: 0.021383, Train_acc: 0.984375 Epoch:4, train_step: 4389, loss: 0.065455, Train_acc: 0.984375 Epoch:4, train_step: 4390, loss: 0.017396, Train_acc: 1.000000 Epoch:4, train_step: 4391, loss: 0.000816, Train_acc: 1.000000 Epoch:4, train_step: 4392, loss: 0.019795, Train_acc: 0.984375 Epoch:4, train_step: 4393, loss: 0.004781, Train_acc: 1.000000 Epoch:4, train_step: 4394, loss: 0.015489, Train_acc: 1.000000 Epoch:4, train_step: 4395, loss: 0.025957, Train_acc: 0.984375 Epoch:4, train_step: 4396, loss: 0.009970, Train_acc: 1.000000 Epoch:4, train_step: 4397, loss: 0.018733, Train_acc: 1.000000 Epoch:4, train_step: 4398, loss: 0.038645, Train_acc: 0.984375 Epoch:4, train_step: 4399, loss: 0.003904, Train_acc: 1.000000 Epoch:4, train_step: 4400, loss: 0.002923, Train_acc: 1.000000 Epoch:4, train_step: 4401, loss: 0.017362, Train_acc: 0.984375 Epoch:4, train_step: 4402, loss: 0.009425, Train_acc: 1.000000 Epoch:4, train_step: 4403, loss: 0.038452, Train_acc: 0.968750 Epoch:4, train_step: 4404, loss: 0.002475, Train_acc: 1.000000 Epoch:4, train_step: 4405, loss: 0.008104, Train_acc: 1.000000 Epoch:4, train_step: 4406, loss: 0.001445, Train_acc: 1.000000 Epoch:4, train_step: 4407, loss: 0.003184, Train_acc: 1.000000 Epoch:4, train_step: 4408, loss: 0.008278, Train_acc: 1.000000 Epoch:4, train_step: 4409, loss: 0.002172, Train_acc: 1.000000 Epoch:4, train_step: 4410, loss: 0.014837, Train_acc: 0.984375 Epoch:4, train_step: 4411, loss: 0.015060, Train_acc: 1.000000 Epoch:4, train_step: 4412, loss: 0.015491, Train_acc: 1.000000 Epoch:4, train_step: 4413, loss: 0.002131, Train_acc: 1.000000 Epoch:4, train_step: 4414, loss: 0.052669, Train_acc: 0.984375 Epoch:4, train_step: 4415, loss: 0.031621, Train_acc: 0.984375 Epoch:4, train_step: 4416, loss: 0.002840, Train_acc: 1.000000 Epoch:4, train_step: 4417, loss: 0.009069, Train_acc: 1.000000 Epoch:4, train_step: 4418, loss: 0.059067, Train_acc: 0.984375 Epoch:4, train_step: 4419, loss: 0.022650, Train_acc: 0.984375 Epoch:4, train_step: 4420, loss: 0.015971, Train_acc: 0.984375 Epoch:4, train_step: 4421, loss: 0.018231, Train_acc: 1.000000 Epoch:4, train_step: 4422, loss: 0.142656, Train_acc: 0.984375 Epoch:4, train_step: 4423, loss: 0.010590, Train_acc: 1.000000 Epoch:4, train_step: 4424, loss: 0.003193, Train_acc: 1.000000 Epoch:4, train_step: 4425, loss: 0.006119, Train_acc: 1.000000 Epoch:4, train_step: 4426, loss: 0.004708, Train_acc: 1.000000 Epoch:4, train_step: 4427, loss: 0.140235, Train_acc: 0.984375 Epoch:4, train_step: 4428, loss: 0.019421, Train_acc: 0.984375 Epoch:4, train_step: 4429, loss: 0.013262, Train_acc: 1.000000 Epoch:4, train_step: 4430, loss: 0.006697, Train_acc: 1.000000 Epoch:4, train_step: 4431, loss: 0.055443, Train_acc: 0.984375 Epoch:4, train_step: 4432, loss: 0.001742, Train_acc: 1.000000 Epoch:4, train_step: 4433, loss: 0.002174, Train_acc: 1.000000 Epoch:4, train_step: 4434, loss: 0.034062, Train_acc: 0.984375 Epoch:4, train_step: 4435, loss: 0.036806, Train_acc: 0.984375 Epoch:4, train_step: 4436, loss: 0.004285, Train_acc: 1.000000 Epoch:4, train_step: 4437, loss: 0.054347, Train_acc: 0.968750 Epoch:4, train_step: 4438, loss: 0.004131, Train_acc: 1.000000 Epoch:4, train_step: 4439, loss: 0.001479, Train_acc: 1.000000 Epoch:4, train_step: 4440, loss: 0.009222, Train_acc: 1.000000 Epoch:4, train_step: 4441, loss: 0.003496, Train_acc: 1.000000 Epoch:4, train_step: 4442, loss: 0.002545, Train_acc: 1.000000 Epoch:4, train_step: 4443, loss: 0.007368, Train_acc: 1.000000 Epoch:4, train_step: 4444, loss: 0.004074, Train_acc: 1.000000 Epoch:4, train_step: 4445, loss: 0.000452, Train_acc: 1.000000 Epoch:4, train_step: 4446, loss: 0.005274, Train_acc: 1.000000 Epoch:4, train_step: 4447, loss: 0.006994, Train_acc: 1.000000 Epoch:4, train_step: 4448, loss: 0.012617, Train_acc: 1.000000 Epoch:4, train_step: 4449, loss: 0.010407, Train_acc: 1.000000 Epoch:4, train_step: 4450, loss: 0.002444, Train_acc: 1.000000 Epoch:4, train_step: 4451, loss: 0.001839, Train_acc: 1.000000 Epoch:4, train_step: 4452, loss: 0.008537, Train_acc: 1.000000 Epoch:4, train_step: 4453, loss: 0.001095, Train_acc: 1.000000 Epoch:4, train_step: 4454, loss: 0.037107, Train_acc: 0.984375 Epoch:4, train_step: 4455, loss: 0.001882, Train_acc: 1.000000 Epoch:4, train_step: 4456, loss: 0.004659, Train_acc: 1.000000 Epoch:4, train_step: 4457, loss: 0.093999, Train_acc: 0.984375 Epoch:4, train_step: 4458, loss: 0.002812, Train_acc: 1.000000 Epoch:4, train_step: 4459, loss: 0.002653, Train_acc: 1.000000 Epoch:4, train_step: 4460, loss: 0.019578, Train_acc: 0.984375 Epoch:4, train_step: 4461, loss: 0.032920, Train_acc: 0.984375 Epoch:4, train_step: 4462, loss: 0.011780, Train_acc: 1.000000 Epoch:4, train_step: 4463, loss: 0.000692, Train_acc: 1.000000 Epoch:4, train_step: 4464, loss: 0.011267, Train_acc: 1.000000 Epoch:4, train_step: 4465, loss: 0.037887, Train_acc: 0.984375 Epoch:4, train_step: 4466, loss: 0.005328, Train_acc: 1.000000 Epoch:4, train_step: 4467, loss: 0.017671, Train_acc: 0.984375 Epoch:4, train_step: 4468, loss: 0.066780, Train_acc: 0.968750 Epoch:4, train_step: 4469, loss: 0.004378, Train_acc: 1.000000 Epoch:4, train_step: 4470, loss: 0.006495, Train_acc: 1.000000 Epoch:4, train_step: 4471, loss: 0.025913, Train_acc: 1.000000 Epoch:4, train_step: 4472, loss: 0.008711, Train_acc: 1.000000 Epoch:4, train_step: 4473, loss: 0.007264, Train_acc: 1.000000 Epoch:4, train_step: 4474, loss: 0.006384, Train_acc: 1.000000 Epoch:4, train_step: 4475, loss: 0.001973, Train_acc: 1.000000 Epoch:4, train_step: 4476, loss: 0.004236, Train_acc: 1.000000 Epoch:4, train_step: 4477, loss: 0.006345, Train_acc: 1.000000 Epoch:4, train_step: 4478, loss: 0.004569, Train_acc: 1.000000 Epoch:4, train_step: 4479, loss: 0.015853, Train_acc: 0.984375 Epoch:4, train_step: 4480, loss: 0.005192, Train_acc: 1.000000 Epoch:4, train_step: 4481, loss: 0.063347, Train_acc: 0.984375 Epoch:4, train_step: 4482, loss: 0.001911, Train_acc: 1.000000 Epoch:4, train_step: 4483, loss: 0.006620, Train_acc: 1.000000 Epoch:4, train_step: 4484, loss: 0.002039, Train_acc: 1.000000 Epoch:4, train_step: 4485, loss: 0.042262, Train_acc: 0.984375 Epoch:4, train_step: 4486, loss: 0.005348, Train_acc: 1.000000 Epoch:4, train_step: 4487, loss: 0.026577, Train_acc: 1.000000 Epoch:4, train_step: 4488, loss: 0.013207, Train_acc: 1.000000 Epoch:4, train_step: 4489, loss: 0.018635, Train_acc: 0.984375 Epoch:4, train_step: 4490, loss: 0.026928, Train_acc: 0.984375 Epoch:4, train_step: 4491, loss: 0.001754, Train_acc: 1.000000 Epoch:4, train_step: 4492, loss: 0.040337, Train_acc: 0.984375 Epoch:4, train_step: 4493, loss: 0.002657, Train_acc: 1.000000 Epoch:4, train_step: 4494, loss: 0.027132, Train_acc: 0.984375 Epoch:4, train_step: 4495, loss: 0.013280, Train_acc: 1.000000 Epoch:4, train_step: 4496, loss: 0.002108, Train_acc: 1.000000 Epoch:4, train_step: 4497, loss: 0.013477, Train_acc: 1.000000 Epoch:4, train_step: 4498, loss: 0.014099, Train_acc: 1.000000 Epoch:4, train_step: 4499, loss: 0.021984, Train_acc: 0.984375 Epoch:4, train_step: 4500, loss: 0.043356, Train_acc: 0.968750 Epoch:4, train_step: 4501, loss: 0.000847, Train_acc: 1.000000 Epoch:4, train_step: 4502, loss: 0.007909, Train_acc: 1.000000 Epoch:4, train_step: 4503, loss: 0.009316, Train_acc: 1.000000 Epoch:4, train_step: 4504, loss: 0.020021, Train_acc: 0.984375 Epoch:4, train_step: 4505, loss: 0.001537, Train_acc: 1.000000 Epoch:4, train_step: 4506, loss: 0.031299, Train_acc: 0.984375 Epoch:4, train_step: 4507, loss: 0.004188, Train_acc: 1.000000 Epoch:4, train_step: 4508, loss: 0.015510, Train_acc: 1.000000 Epoch:4, train_step: 4509, loss: 0.032228, Train_acc: 0.984375 Epoch:4, train_step: 4510, loss: 0.038235, Train_acc: 0.984375 Epoch:4, train_step: 4511, loss: 0.006475, Train_acc: 1.000000 Epoch:4, train_step: 4512, loss: 0.008101, Train_acc: 1.000000 Epoch:4, train_step: 4513, loss: 0.172209, Train_acc: 0.984375 Epoch:4, train_step: 4514, loss: 0.053055, Train_acc: 0.968750 Epoch:4, train_step: 4515, loss: 0.098359, Train_acc: 0.968750 Epoch:4, train_step: 4516, loss: 0.000864, Train_acc: 1.000000 Epoch:4, train_step: 4517, loss: 0.099131, Train_acc: 0.968750 Epoch:4, train_step: 4518, loss: 0.002585, Train_acc: 1.000000 Epoch:4, train_step: 4519, loss: 0.002596, Train_acc: 1.000000 Epoch:4, train_step: 4520, loss: 0.007240, Train_acc: 1.000000 Epoch:4, train_step: 4521, loss: 0.032530, Train_acc: 0.968750 Epoch:4, train_step: 4522, loss: 0.032581, Train_acc: 0.984375 Epoch:4, train_step: 4523, loss: 0.005516, Train_acc: 1.000000 Epoch:4, train_step: 4524, loss: 0.004626, Train_acc: 1.000000 Epoch:4, train_step: 4525, loss: 0.002067, Train_acc: 1.000000 Epoch:4, train_step: 4526, loss: 0.007212, Train_acc: 1.000000 Epoch:4, train_step: 4527, loss: 0.004827, Train_acc: 1.000000 Epoch:4, train_step: 4528, loss: 0.025258, Train_acc: 0.984375 Epoch:4, train_step: 4529, loss: 0.003282, Train_acc: 1.000000 Epoch:4, train_step: 4530, loss: 0.003226, Train_acc: 1.000000 Epoch:4, train_step: 4531, loss: 0.004611, Train_acc: 1.000000 Epoch:4, train_step: 4532, loss: 0.002960, Train_acc: 1.000000 Epoch:4, train_step: 4533, loss: 0.001629, Train_acc: 1.000000 Epoch:4, train_step: 4534, loss: 0.000260, Train_acc: 1.000000 Epoch:4, train_step: 4535, loss: 0.003174, Train_acc: 1.000000 Epoch:4, train_step: 4536, loss: 0.010497, Train_acc: 1.000000 Epoch:4, train_step: 4537, loss: 0.053527, Train_acc: 0.984375 Epoch:4, train_step: 4538, loss: 0.004257, Train_acc: 1.000000 Epoch:4, train_step: 4539, loss: 0.017497, Train_acc: 1.000000 Epoch:4, train_step: 4540, loss: 0.000202, Train_acc: 1.000000 Epoch:4, train_step: 4541, loss: 0.004066, Train_acc: 1.000000 Epoch:4, train_step: 4542, loss: 0.000568, Train_acc: 1.000000 Epoch:4, train_step: 4543, loss: 0.001151, Train_acc: 1.000000 Epoch:4, train_step: 4544, loss: 0.016735, Train_acc: 1.000000 Epoch:4, train_step: 4545, loss: 0.016120, Train_acc: 1.000000 Epoch:4, train_step: 4546, loss: 0.002930, Train_acc: 1.000000 Epoch:4, train_step: 4547, loss: 0.010299, Train_acc: 1.000000 Epoch:4, train_step: 4548, loss: 0.001160, Train_acc: 1.000000 Epoch:4, train_step: 4549, loss: 0.019655, Train_acc: 1.000000 Epoch:4, train_step: 4550, loss: 0.006685, Train_acc: 1.000000 Epoch:4, train_step: 4551, loss: 0.002230, Train_acc: 1.000000 Epoch:4, train_step: 4552, loss: 0.004235, Train_acc: 1.000000 Epoch:4, train_step: 4553, loss: 0.005311, Train_acc: 1.000000 Epoch:4, train_step: 4554, loss: 0.011384, Train_acc: 1.000000 Epoch:4, train_step: 4555, loss: 0.013399, Train_acc: 1.000000 Epoch:4, train_step: 4556, loss: 0.018525, Train_acc: 1.000000 Epoch:4, train_step: 4557, loss: 0.005084, Train_acc: 1.000000 Epoch:4, train_step: 4558, loss: 0.004482, Train_acc: 1.000000 Epoch:4, train_step: 4559, loss: 0.000238, Train_acc: 1.000000 Epoch:4, train_step: 4560, loss: 0.125593, Train_acc: 0.984375 Epoch:4, train_step: 4561, loss: 0.030978, Train_acc: 1.000000 Epoch:4, train_step: 4562, loss: 0.002856, Train_acc: 1.000000 Epoch:4, train_step: 4563, loss: 0.015316, Train_acc: 1.000000 Epoch:4, train_step: 4564, loss: 0.003299, Train_acc: 1.000000 Epoch:4, train_step: 4565, loss: 0.005323, Train_acc: 1.000000 Epoch:4, train_step: 4566, loss: 0.004487, Train_acc: 1.000000 Epoch:4, train_step: 4567, loss: 0.002876, Train_acc: 1.000000 Epoch:4, train_step: 4568, loss: 0.003537, Train_acc: 1.000000 Epoch:4, train_step: 4569, loss: 0.003676, Train_acc: 1.000000 Epoch:4, train_step: 4570, loss: 0.001119, Train_acc: 1.000000 Epoch:4, train_step: 4571, loss: 0.000599, Train_acc: 1.000000 Epoch:4, train_step: 4572, loss: 0.001054, Train_acc: 1.000000 Epoch:4, train_step: 4573, loss: 0.005624, Train_acc: 1.000000 Epoch:4, train_step: 4574, loss: 0.017939, Train_acc: 1.000000 Epoch:4, train_step: 4575, loss: 0.028901, Train_acc: 0.984375 Epoch:4, train_step: 4576, loss: 0.113929, Train_acc: 0.984375 Epoch:4, train_step: 4577, loss: 0.001556, Train_acc: 1.000000 Epoch:4, train_step: 4578, loss: 0.021931, Train_acc: 0.984375 Epoch:4, train_step: 4579, loss: 0.005304, Train_acc: 1.000000 Epoch:4, train_step: 4580, loss: 0.001043, Train_acc: 1.000000 Epoch:4, train_step: 4581, loss: 0.000678, Train_acc: 1.000000 Epoch:4, train_step: 4582, loss: 0.000517, Train_acc: 1.000000 Epoch:4, train_step: 4583, loss: 0.062325, Train_acc: 0.984375 Epoch:4, train_step: 4584, loss: 0.005431, Train_acc: 1.000000 Epoch:4, train_step: 4585, loss: 0.001240, Train_acc: 1.000000 Epoch:4, train_step: 4586, loss: 0.000731, Train_acc: 1.000000 Epoch:4, train_step: 4587, loss: 0.042454, Train_acc: 0.968750 Epoch:4, train_step: 4588, loss: 0.013803, Train_acc: 0.984375 Epoch:4, train_step: 4589, loss: 0.005095, Train_acc: 1.000000 Epoch:4, train_step: 4590, loss: 0.009731, Train_acc: 1.000000 Epoch:4, train_step: 4591, loss: 0.003930, Train_acc: 1.000000 Epoch:4, train_step: 4592, loss: 0.006254, Train_acc: 1.000000 Epoch:4, train_step: 4593, loss: 0.019605, Train_acc: 0.984375 Epoch:4, train_step: 4594, loss: 0.006940, Train_acc: 1.000000 Epoch:4, train_step: 4595, loss: 0.001667, Train_acc: 1.000000 Epoch:4, train_step: 4596, loss: 0.010604, Train_acc: 1.000000 Epoch:4, train_step: 4597, loss: 0.003742, Train_acc: 1.000000 Epoch:4, train_step: 4598, loss: 0.002476, Train_acc: 1.000000 Epoch:4, train_step: 4599, loss: 0.061072, Train_acc: 0.984375 Epoch:4, train_step: 4600, loss: 0.006573, Train_acc: 1.000000 Epoch:4, train_step: 4601, loss: 0.028051, Train_acc: 0.984375 Epoch:4, train_step: 4602, loss: 0.010519, Train_acc: 1.000000 Epoch:4, train_step: 4603, loss: 0.001819, Train_acc: 1.000000 Epoch:4, train_step: 4604, loss: 0.011131, Train_acc: 1.000000 Epoch:4, train_step: 4605, loss: 0.015042, Train_acc: 1.000000 Epoch:4, train_step: 4606, loss: 0.025956, Train_acc: 1.000000 Epoch:4, train_step: 4607, loss: 0.005424, Train_acc: 1.000000 Epoch:4, train_step: 4608, loss: 0.000552, Train_acc: 1.000000 Epoch:4, train_step: 4609, loss: 0.001574, Train_acc: 1.000000 Epoch:4, train_step: 4610, loss: 0.002414, Train_acc: 1.000000 Epoch:4, train_step: 4611, loss: 0.058362, Train_acc: 0.984375 Epoch:4, train_step: 4612, loss: 0.015419, Train_acc: 1.000000 Epoch:4, train_step: 4613, loss: 0.045299, Train_acc: 0.968750 Epoch:4, train_step: 4614, loss: 0.036246, Train_acc: 0.984375 Epoch:4, train_step: 4615, loss: 0.014974, Train_acc: 0.984375 Epoch:4, train_step: 4616, loss: 0.005563, Train_acc: 1.000000 Epoch:4, train_step: 4617, loss: 0.063160, Train_acc: 0.984375 Epoch:4, train_step: 4618, loss: 0.003169, Train_acc: 1.000000 Epoch:4, train_step: 4619, loss: 0.013708, Train_acc: 1.000000 Epoch:4, train_step: 4620, loss: 0.004433, Train_acc: 1.000000 Epoch:4, train_step: 4621, loss: 0.018232, Train_acc: 1.000000 Epoch:4, train_step: 4622, loss: 0.004088, Train_acc: 1.000000 Epoch:4, train_step: 4623, loss: 0.004904, Train_acc: 1.000000 Epoch:4, train_step: 4624, loss: 0.014987, Train_acc: 1.000000 Epoch:4, train_step: 4625, loss: 0.003224, Train_acc: 1.000000 Epoch:4, train_step: 4626, loss: 0.065013, Train_acc: 0.984375 Epoch:4, train_step: 4627, loss: 0.015311, Train_acc: 0.984375 Epoch:4, train_step: 4628, loss: 0.008445, Train_acc: 1.000000 Epoch:4, train_step: 4629, loss: 0.006273, Train_acc: 1.000000 Epoch:4, train_step: 4630, loss: 0.015948, Train_acc: 1.000000 Epoch:4, train_step: 4631, loss: 0.013378, Train_acc: 1.000000 Epoch:4, train_step: 4632, loss: 0.003214, Train_acc: 1.000000 Epoch:4, train_step: 4633, loss: 0.005450, Train_acc: 1.000000 Epoch:4, train_step: 4634, loss: 0.006493, Train_acc: 1.000000 Epoch:4, train_step: 4635, loss: 0.001834, Train_acc: 1.000000 Epoch:4, train_step: 4636, loss: 0.024179, Train_acc: 0.984375 Epoch:4, train_step: 4637, loss: 0.022755, Train_acc: 0.984375 Epoch:4, train_step: 4638, loss: 0.000265, Train_acc: 1.000000 Epoch:4, train_step: 4639, loss: 0.002019, Train_acc: 1.000000 Epoch:4, train_step: 4640, loss: 0.008307, Train_acc: 1.000000 Epoch:4, train_step: 4641, loss: 0.000571, Train_acc: 1.000000 Epoch:4, train_step: 4642, loss: 0.002582, Train_acc: 1.000000 Epoch:4, train_step: 4643, loss: 0.043802, Train_acc: 0.984375 Epoch:4, train_step: 4644, loss: 0.005830, Train_acc: 1.000000 Epoch:4, train_step: 4645, loss: 0.032212, Train_acc: 0.984375 Epoch:4, train_step: 4646, loss: 0.009485, Train_acc: 1.000000 Epoch:4, train_step: 4647, loss: 0.024277, Train_acc: 0.984375 Epoch:4, train_step: 4648, loss: 0.001220, Train_acc: 1.000000 Epoch:4, train_step: 4649, loss: 0.009742, Train_acc: 1.000000 Epoch:4, train_step: 4650, loss: 0.003131, Train_acc: 1.000000 Epoch:4, train_step: 4651, loss: 0.076755, Train_acc: 0.984375 Epoch:4, train_step: 4652, loss: 0.041819, Train_acc: 0.968750 Epoch:4, train_step: 4653, loss: 0.007329, Train_acc: 1.000000 Epoch:4, train_step: 4654, loss: 0.024101, Train_acc: 1.000000 Epoch:4, train_step: 4655, loss: 0.029153, Train_acc: 0.984375 Epoch:4, train_step: 4656, loss: 0.065994, Train_acc: 0.984375 Epoch:4, train_step: 4657, loss: 0.000176, Train_acc: 1.000000 Epoch:4, train_step: 4658, loss: 0.001461, Train_acc: 1.000000 Epoch:4, train_step: 4659, loss: 0.000234, Train_acc: 1.000000 Epoch:4, train_step: 4660, loss: 0.002864, Train_acc: 1.000000 Epoch:4, train_step: 4661, loss: 0.001337, Train_acc: 1.000000 Epoch:4, train_step: 4662, loss: 0.000416, Train_acc: 1.000000 Epoch:4, train_step: 4663, loss: 0.000935, Train_acc: 1.000000 Epoch:4, train_step: 4664, loss: 0.001171, Train_acc: 1.000000 Epoch:4, train_step: 4665, loss: 0.024274, Train_acc: 0.984375 Epoch:4, train_step: 4666, loss: 0.000032, Train_acc: 1.000000 Epoch:4, train_step: 4667, loss: 0.002931, Train_acc: 1.000000 Epoch:4, train_step: 4668, loss: 0.011314, Train_acc: 1.000000 Epoch:4, train_step: 4669, loss: 0.001236, Train_acc: 1.000000 Epoch:4, train_step: 4670, loss: 0.000085, Train_acc: 1.000000 Epoch:4, train_step: 4671, loss: 0.000431, Train_acc: 1.000000 Epoch:4, train_step: 4672, loss: 0.000504, Train_acc: 1.000000 Epoch:4, train_step: 4673, loss: 0.000061, Train_acc: 1.000000 Epoch:4, train_step: 4674, loss: 0.000257, Train_acc: 1.000000 Epoch:4, train_step: 4675, loss: 0.006405, Train_acc: 1.000000 Epoch:4, train_step: 4676, loss: 0.008080, Train_acc: 1.000000 Epoch:4, train_step: 4677, loss: 0.000531, Train_acc: 1.000000 Epoch:4, train_step: 4678, loss: 0.020647, Train_acc: 0.984375 Epoch:4, train_step: 4679, loss: 0.000083, Train_acc: 1.000000 Epoch:4, train_step: 4680, loss: 0.001731, Train_acc: 1.000000 Epoch:4, train_step: 4681, loss: 0.003079, Train_acc: 1.000000 Epoch:4, train_step: 4682, loss: 0.095505, Train_acc: 0.968750 Epoch:4, train_step: 4683, loss: 0.002659, Train_acc: 1.000000 Epoch:4, train_step: 4684, loss: 0.000122, Train_acc: 1.000000 Epoch:4, train_step: 4685, loss: 0.185106, Train_acc: 0.984375 Epoch:4, avg_train_loss: 0.017215, avg_train_acc: 0.994731, Test_acc: 0.985677

mxnet框架下超全手写字体识别—从数据预处理到网络的训练—模型