In [0]:
"""
We use following lines because we are running on Google Colab
If you are running notebook on a local computer, you don't need these
"""
from google.colab import drive
drive.mount('/content/gdrive')
import os
os.chdir('/content/gdrive/My Drive/finch/tensorflow2/text_classification/imdb/main')
Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount("/content/gdrive", force_remount=True).
In [0]:
!pip install tensorflow-gpu==2.0.0-alpha0
Requirement already satisfied: tensorflow-gpu==2.0.0-alpha0 in /usr/local/lib/python3.6/dist-packages (2.0.0a0)
Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.12.0)
Requirement already satisfied: keras-applications>=1.0.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.0.7)
Requirement already satisfied: tf-estimator-nightly<1.14.0.dev2019030116,>=1.14.0.dev2019030115 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.14.0.dev2019030115)
Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.0.9)
Requirement already satisfied: numpy<2.0,>=1.14.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.16.3)
Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.15.0)
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Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.2.2)
Requirement already satisfied: tb-nightly<1.14.0a20190302,>=1.14.0a20190301 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.14.0a20190301)
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Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow-gpu==2.0.0-alpha0) (0.15.4)
Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tensorflow-gpu==2.0.0-alpha0) (41.0.1)
In [0]:
import tensorflow as tf
import numpy as np
import pprint
import logging
import time

print("TensorFlow Version", tf.__version__)
print('GPU Enabled:', tf.test.is_gpu_available())
TensorFlow Version 2.0.0-alpha0
GPU Enabled: True
In [0]:
def data_generator(f_path, params):
  with open(f_path) as f:
    print('Reading', f_path)
    for line in f:
      line = line.rstrip()
      label, text = line.split('\t')
      text = text.split(' ')
      x = [params['word2idx'].get(w, len(word2idx)) for w in text]
      if len(x) >= params['max_len']:
        x = x[:params['max_len']]
      else:
        x += [0] * (params['max_len'] - len(x))
      y = int(label)
      yield x, y


def dataset(is_training, params):
  _shapes = ([params['max_len']], ())
  _types = (tf.int32, tf.int32)
  
  if is_training:
    ds = tf.data.Dataset.from_generator(
      lambda: data_generator(params['train_path'], params),
      output_shapes = _shapes,
      output_types = _types,)
    ds = ds.shuffle(params['num_samples'])
    ds = ds.batch(params['batch_size'])
    ds = ds.prefetch(tf.data.experimental.AUTOTUNE)
  else:
    ds = tf.data.Dataset.from_generator(
      lambda: data_generator(params['test_path'], params),
      output_shapes = _shapes,
      output_types = _types,)
    ds = ds.batch(params['batch_size'])
    ds = ds.prefetch(tf.data.experimental.AUTOTUNE)
  
  return ds
In [0]:
class Model(tf.keras.Model):
  def __init__(self, params):
    super().__init__()
    
    self.embedding = tf.Variable(np.load('../vocab/word.npy'),
                                 dtype=tf.float32,
                                 name='pretrained_embedding',
                                 trainable=False,)
    
    self.drop1 = tf.keras.layers.Dropout(params['dropout_rate'])
    self.drop2 = tf.keras.layers.Dropout(params['dropout_rate'])
    self.drop3 = tf.keras.layers.Dropout(params['dropout_rate'])
    
    self.rnn1 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(params['rnn_units'], return_sequences=True))
    self.rnn2 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(params['rnn_units'], return_sequences=True))
    self.rnn3 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(params['rnn_units'], return_sequences=True))
    
    self.drop_fc = tf.keras.layers.Dropout(params['dropout_rate'])
    self.fc = tf.keras.layers.Dense(2*params['rnn_units'], tf.nn.elu)
    
    self.out_linear = tf.keras.layers.Dense(2)
  
  
  def call(self, inputs, training=False):
    if inputs.dtype != tf.int32:
      inputs = tf.cast(inputs, tf.int32)
    
    batch_sz = tf.shape(inputs)[0]
    rnn_units = 2*params['rnn_units']
    
    x = tf.nn.embedding_lookup(self.embedding, inputs)
    
    x = tf.reshape(x, (batch_sz*10*10, 10, 300))
    x = self.drop1(x, training=training)
    x = self.rnn1(x)
    x = tf.reduce_max(x, 1)
    
    x = tf.reshape(x, (batch_sz*10, 10, rnn_units))
    x = self.drop2(x, training=training)
    x = self.rnn2(x)
    x = tf.reduce_max(x, 1)
    
    x = tf.reshape(x, (batch_sz, 10, rnn_units))
    x = self.drop3(x, training=training)
    x = self.rnn3(x)
    x = tf.reduce_max(x, 1)
    
    x = self.drop_fc(x, training=training)
    x = self.fc(x)
    
    x = self.out_linear(x)
    
    return x
In [0]:
params = {
  'vocab_path': '../vocab/word.txt',
  'train_path': '../data/train.txt',
  'test_path': '../data/test.txt',
  'num_samples': 25000,
  'num_labels': 2,
  'batch_size': 32,
  'max_len': 1000,
  'rnn_units': 200,
  'dropout_rate': 0.2,
  'clip_norm': 10.,
  'num_patience': 3,
  'lr': 3e-4,
}
In [0]:
def is_descending(history: list):
  history = history[-(params['num_patience']+1):]
  for i in range(1, len(history)):
    if history[i-1] <= history[i]:
      return False
  return True    
In [0]:
word2idx = {}
with open(params['vocab_path']) as f:
  for i, line in enumerate(f):
    line = line.rstrip()
    word2idx[line] = i
params['word2idx'] = word2idx
params['vocab_size'] = len(word2idx) + 1


model = Model(params)
model.build(input_shape=(None, None))
pprint.pprint([(v.name, v.shape) for v in model.trainable_variables])

decay_lr = tf.optimizers.schedules.ExponentialDecay(params['lr'], 1000, 0.95)
optim = tf.optimizers.Adam(params['lr'])
global_step = 0

history_acc = []
best_acc = .0

t0 = time.time()
logger = logging.getLogger('tensorflow')
logger.setLevel(logging.INFO)


while True:
  # TRAINING
  for texts, labels in dataset(is_training=True, params=params):
    with tf.GradientTape() as tape:
      logits = model(texts, training=True)
      loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=labels, logits=logits)
      loss = tf.reduce_mean(loss)
  
    optim.lr.assign(decay_lr(global_step))
    grads = tape.gradient(loss, model.trainable_variables)
    grads, _ = tf.clip_by_global_norm(grads, params['clip_norm'])
    optim.apply_gradients(zip(grads, model.trainable_variables))

    if global_step % 50 == 0:
      logger.info("Step {} | Loss: {:.4f} | Spent: {:.1f} secs | LR: {:.6f}".format(
          global_step, loss.numpy().item(), time.time()-t0, optim.lr.numpy().item()))
      t0 = time.time()
    global_step += 1

  # EVALUATION
  m = tf.keras.metrics.Accuracy()

  for texts, labels in dataset(is_training=False, params=params):
    logits = model(texts, training=False)
    y_pred = tf.argmax(logits, axis=-1)
    m.update_state(y_true=labels, y_pred=y_pred)
    
  acc = m.result().numpy()
  logger.info("Evaluation: Testing Accuracy: {:.3f}".format(acc))
  history_acc.append(acc)
  
  if acc > best_acc:
    best_acc = acc
    # you can save model here
  logger.info("Best Accuracy: {:.3f}".format(best_acc))
  
  if len(history_acc) > params['num_patience'] and is_descending(history_acc):
    logger.info("Testing Accuracy not improved over {} epochs, Early Stop".format(params['num_patience']))
    break
WARNING: Logging before flag parsing goes to stderr.
W0522 06:00:16.128928 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb1707e2588>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.136606 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb1707e2ba8>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.143041 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb1707962e8>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.147958 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb170796a58>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.152568 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb1707a8198>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.156378 140402235246464 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fb1707a8908>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
W0522 06:00:16.716629 140402235246464 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/data/ops/dataset_ops.py:410: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
    options available in V2.
    - tf.py_function takes a python function which manipulates tf eager
    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
    an ndarray (just call tensor.numpy()) but having access to eager tensors
    means `tf.py_function`s can use accelerators such as GPUs as well as
    being differentiable using a gradient tape.
    - tf.numpy_function maintains the semantics of the deprecated tf.py_func
    (it is not differentiable, and manipulates numpy arrays). It drops the
    stateful argument making all functions stateful.
    
[('bidirectional/forward_unified_lstm/kernel:0', TensorShape([300, 800])),
 ('bidirectional/forward_unified_lstm/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional/forward_unified_lstm/bias:0', TensorShape([800])),
 ('bidirectional/backward_unified_lstm/kernel:0', TensorShape([300, 800])),
 ('bidirectional/backward_unified_lstm/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional/backward_unified_lstm/bias:0', TensorShape([800])),
 ('bidirectional_1/forward_unified_lstm_1/kernel:0', TensorShape([400, 800])),
 ('bidirectional_1/forward_unified_lstm_1/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional_1/forward_unified_lstm_1/bias:0', TensorShape([800])),
 ('bidirectional_1/backward_unified_lstm_1/kernel:0', TensorShape([400, 800])),
 ('bidirectional_1/backward_unified_lstm_1/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional_1/backward_unified_lstm_1/bias:0', TensorShape([800])),
 ('bidirectional_2/forward_unified_lstm_2/kernel:0', TensorShape([400, 800])),
 ('bidirectional_2/forward_unified_lstm_2/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional_2/forward_unified_lstm_2/bias:0', TensorShape([800])),
 ('bidirectional_2/backward_unified_lstm_2/kernel:0', TensorShape([400, 800])),
 ('bidirectional_2/backward_unified_lstm_2/recurrent_kernel:0',
  TensorShape([200, 800])),
 ('bidirectional_2/backward_unified_lstm_2/bias:0', TensorShape([800])),
 ('dense/kernel:0', TensorShape([400, 400])),
 ('dense/bias:0', TensorShape([400])),
 ('dense_1/kernel:0', TensorShape([400, 2])),
 ('dense_1/bias:0', TensorShape([2]))]
Reading ../data/train.txt
I0522 06:00:28.101212 140402235246464 interactiveshell.py:2882] Step 0 | Loss: 0.6899 | Spent: 11.4 secs | LR: 0.000300
I0522 06:00:35.173103 140402235246464 interactiveshell.py:2882] Step 50 | Loss: 0.5973 | Spent: 7.1 secs | LR: 0.000299
I0522 06:00:42.280910 140402235246464 interactiveshell.py:2882] Step 100 | Loss: 0.3981 | Spent: 7.1 secs | LR: 0.000298
I0522 06:00:49.552725 140402235246464 interactiveshell.py:2882] Step 150 | Loss: 0.3995 | Spent: 7.3 secs | LR: 0.000298
I0522 06:00:56.419491 140402235246464 interactiveshell.py:2882] Step 200 | Loss: 0.2604 | Spent: 6.9 secs | LR: 0.000297
I0522 06:01:03.299215 140402235246464 interactiveshell.py:2882] Step 250 | Loss: 0.2755 | Spent: 6.9 secs | LR: 0.000296
I0522 06:01:10.227056 140402235246464 interactiveshell.py:2882] Step 300 | Loss: 0.3494 | Spent: 6.9 secs | LR: 0.000295
I0522 06:01:17.067388 140402235246464 interactiveshell.py:2882] Step 350 | Loss: 0.3153 | Spent: 6.8 secs | LR: 0.000295
I0522 06:01:23.921555 140402235246464 interactiveshell.py:2882] Step 400 | Loss: 0.3775 | Spent: 6.9 secs | LR: 0.000294
I0522 06:01:30.742784 140402235246464 interactiveshell.py:2882] Step 450 | Loss: 0.3860 | Spent: 6.8 secs | LR: 0.000293
I0522 06:01:37.594786 140402235246464 interactiveshell.py:2882] Step 500 | Loss: 0.1914 | Spent: 6.9 secs | LR: 0.000292
I0522 06:01:44.419071 140402235246464 interactiveshell.py:2882] Step 550 | Loss: 0.4004 | Spent: 6.8 secs | LR: 0.000292
I0522 06:01:51.262611 140402235246464 interactiveshell.py:2882] Step 600 | Loss: 0.3732 | Spent: 6.8 secs | LR: 0.000291
I0522 06:01:58.057201 140402235246464 interactiveshell.py:2882] Step 650 | Loss: 0.2745 | Spent: 6.8 secs | LR: 0.000290
I0522 06:02:05.376116 140402235246464 interactiveshell.py:2882] Step 700 | Loss: 0.2110 | Spent: 7.3 secs | LR: 0.000289
I0522 06:02:12.458704 140402235246464 interactiveshell.py:2882] Step 750 | Loss: 0.3655 | Spent: 7.1 secs | LR: 0.000289
Reading ../data/test.txt
I0522 06:04:00.811849 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.872
I0522 06:04:00.812934 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.872
Reading ../data/train.txt
I0522 06:04:11.099680 140402235246464 interactiveshell.py:2882] Step 800 | Loss: 0.1838 | Spent: 118.6 secs | LR: 0.000288
I0522 06:04:18.193276 140402235246464 interactiveshell.py:2882] Step 850 | Loss: 0.1960 | Spent: 7.1 secs | LR: 0.000287
I0522 06:04:25.036258 140402235246464 interactiveshell.py:2882] Step 900 | Loss: 0.2801 | Spent: 6.8 secs | LR: 0.000286
I0522 06:04:31.920581 140402235246464 interactiveshell.py:2882] Step 950 | Loss: 0.3964 | Spent: 6.9 secs | LR: 0.000286
I0522 06:04:38.781151 140402235246464 interactiveshell.py:2882] Step 1000 | Loss: 0.4157 | Spent: 6.9 secs | LR: 0.000285
I0522 06:04:46.005569 140402235246464 interactiveshell.py:2882] Step 1050 | Loss: 0.3943 | Spent: 7.2 secs | LR: 0.000284
I0522 06:04:53.096568 140402235246464 interactiveshell.py:2882] Step 1100 | Loss: 0.1811 | Spent: 7.1 secs | LR: 0.000284
I0522 06:04:59.896063 140402235246464 interactiveshell.py:2882] Step 1150 | Loss: 0.3176 | Spent: 6.8 secs | LR: 0.000283
I0522 06:05:06.716237 140402235246464 interactiveshell.py:2882] Step 1200 | Loss: 0.2365 | Spent: 6.8 secs | LR: 0.000282
I0522 06:05:13.533614 140402235246464 interactiveshell.py:2882] Step 1250 | Loss: 0.3536 | Spent: 6.8 secs | LR: 0.000281
I0522 06:05:20.417361 140402235246464 interactiveshell.py:2882] Step 1300 | Loss: 0.2620 | Spent: 6.9 secs | LR: 0.000281
I0522 06:05:27.243631 140402235246464 interactiveshell.py:2882] Step 1350 | Loss: 0.4531 | Spent: 6.8 secs | LR: 0.000280
I0522 06:05:34.827698 140402235246464 interactiveshell.py:2882] Step 1400 | Loss: 0.1841 | Spent: 7.6 secs | LR: 0.000279
I0522 06:05:41.934281 140402235246464 interactiveshell.py:2882] Step 1450 | Loss: 0.3515 | Spent: 7.1 secs | LR: 0.000278
I0522 06:05:48.730465 140402235246464 interactiveshell.py:2882] Step 1500 | Loss: 0.4069 | Spent: 6.8 secs | LR: 0.000278
I0522 06:05:55.579224 140402235246464 interactiveshell.py:2882] Step 1550 | Loss: 0.2197 | Spent: 6.8 secs | LR: 0.000277
Reading ../data/test.txt
I0522 06:07:43.578926 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.892
I0522 06:07:43.580015 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.892
Reading ../data/train.txt
I0522 06:07:56.117774 140402235246464 interactiveshell.py:2882] Step 1600 | Loss: 0.3621 | Spent: 120.5 secs | LR: 0.000276
I0522 06:08:02.957704 140402235246464 interactiveshell.py:2882] Step 1650 | Loss: 0.3189 | Spent: 6.8 secs | LR: 0.000276
I0522 06:08:09.869735 140402235246464 interactiveshell.py:2882] Step 1700 | Loss: 0.1686 | Spent: 6.9 secs | LR: 0.000275
I0522 06:08:16.710909 140402235246464 interactiveshell.py:2882] Step 1750 | Loss: 0.2139 | Spent: 6.8 secs | LR: 0.000274
I0522 06:08:23.579322 140402235246464 interactiveshell.py:2882] Step 1800 | Loss: 0.1603 | Spent: 6.9 secs | LR: 0.000274
I0522 06:08:30.422227 140402235246464 interactiveshell.py:2882] Step 1850 | Loss: 0.2287 | Spent: 6.8 secs | LR: 0.000273
I0522 06:08:37.331770 140402235246464 interactiveshell.py:2882] Step 1900 | Loss: 0.2965 | Spent: 6.9 secs | LR: 0.000272
I0522 06:08:44.361136 140402235246464 interactiveshell.py:2882] Step 1950 | Loss: 0.1567 | Spent: 7.0 secs | LR: 0.000271
I0522 06:08:51.658203 140402235246464 interactiveshell.py:2882] Step 2000 | Loss: 0.2704 | Spent: 7.3 secs | LR: 0.000271
I0522 06:08:58.459338 140402235246464 interactiveshell.py:2882] Step 2050 | Loss: 0.3557 | Spent: 6.8 secs | LR: 0.000270
I0522 06:09:05.282869 140402235246464 interactiveshell.py:2882] Step 2100 | Loss: 0.3032 | Spent: 6.8 secs | LR: 0.000269
I0522 06:09:12.172815 140402235246464 interactiveshell.py:2882] Step 2150 | Loss: 0.3330 | Spent: 6.9 secs | LR: 0.000269
I0522 06:09:19.446329 140402235246464 interactiveshell.py:2882] Step 2200 | Loss: 0.1853 | Spent: 7.3 secs | LR: 0.000268
I0522 06:09:26.346133 140402235246464 interactiveshell.py:2882] Step 2250 | Loss: 0.3986 | Spent: 6.9 secs | LR: 0.000267
I0522 06:09:33.261456 140402235246464 interactiveshell.py:2882] Step 2300 | Loss: 0.1232 | Spent: 6.9 secs | LR: 0.000267
Reading ../data/test.txt
I0522 06:11:26.326208 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.896
I0522 06:11:26.327422 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.896
Reading ../data/train.txt
I0522 06:11:35.249225 140402235246464 interactiveshell.py:2882] Step 2350 | Loss: 0.3688 | Spent: 122.0 secs | LR: 0.000266
I0522 06:11:42.102952 140402235246464 interactiveshell.py:2882] Step 2400 | Loss: 0.1792 | Spent: 6.9 secs | LR: 0.000265
I0522 06:11:48.998107 140402235246464 interactiveshell.py:2882] Step 2450 | Loss: 0.3249 | Spent: 6.9 secs | LR: 0.000265
I0522 06:11:55.884904 140402235246464 interactiveshell.py:2882] Step 2500 | Loss: 0.2622 | Spent: 6.9 secs | LR: 0.000264
I0522 06:12:02.802589 140402235246464 interactiveshell.py:2882] Step 2550 | Loss: 0.2555 | Spent: 6.9 secs | LR: 0.000263
I0522 06:12:09.642872 140402235246464 interactiveshell.py:2882] Step 2600 | Loss: 0.1623 | Spent: 6.8 secs | LR: 0.000263
I0522 06:12:16.510231 140402235246464 interactiveshell.py:2882] Step 2650 | Loss: 0.2647 | Spent: 6.9 secs | LR: 0.000262
I0522 06:12:23.342818 140402235246464 interactiveshell.py:2882] Step 2700 | Loss: 0.0874 | Spent: 6.8 secs | LR: 0.000261
I0522 06:12:30.250116 140402235246464 interactiveshell.py:2882] Step 2750 | Loss: 0.4048 | Spent: 6.9 secs | LR: 0.000261
I0522 06:12:37.162192 140402235246464 interactiveshell.py:2882] Step 2800 | Loss: 0.1993 | Spent: 6.9 secs | LR: 0.000260
I0522 06:12:44.148721 140402235246464 interactiveshell.py:2882] Step 2850 | Loss: 0.2429 | Spent: 7.0 secs | LR: 0.000259
I0522 06:12:51.456057 140402235246464 interactiveshell.py:2882] Step 2900 | Loss: 0.2117 | Spent: 7.3 secs | LR: 0.000259
I0522 06:12:58.369017 140402235246464 interactiveshell.py:2882] Step 2950 | Loss: 0.1517 | Spent: 6.9 secs | LR: 0.000258
I0522 06:13:05.215224 140402235246464 interactiveshell.py:2882] Step 3000 | Loss: 0.2161 | Spent: 6.8 secs | LR: 0.000257
I0522 06:13:12.088215 140402235246464 interactiveshell.py:2882] Step 3050 | Loss: 0.1734 | Spent: 6.9 secs | LR: 0.000257
I0522 06:13:18.949706 140402235246464 interactiveshell.py:2882] Step 3100 | Loss: 0.3786 | Spent: 6.9 secs | LR: 0.000256
Reading ../data/test.txt
I0522 06:15:08.915363 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.895
I0522 06:15:08.916345 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.896
Reading ../data/train.txt
I0522 06:15:19.615547 140402235246464 interactiveshell.py:2882] Step 3150 | Loss: 0.2303 | Spent: 120.7 secs | LR: 0.000255
I0522 06:15:26.751202 140402235246464 interactiveshell.py:2882] Step 3200 | Loss: 0.1875 | Spent: 7.1 secs | LR: 0.000255
I0522 06:15:34.087670 140402235246464 interactiveshell.py:2882] Step 3250 | Loss: 0.2479 | Spent: 7.3 secs | LR: 0.000254
I0522 06:15:40.994253 140402235246464 interactiveshell.py:2882] Step 3300 | Loss: 0.2494 | Spent: 6.9 secs | LR: 0.000253
I0522 06:15:47.893201 140402235246464 interactiveshell.py:2882] Step 3350 | Loss: 0.3429 | Spent: 6.9 secs | LR: 0.000253
I0522 06:15:55.491878 140402235246464 interactiveshell.py:2882] Step 3400 | Loss: 0.0906 | Spent: 7.6 secs | LR: 0.000252
I0522 06:16:02.687877 140402235246464 interactiveshell.py:2882] Step 3450 | Loss: 0.5265 | Spent: 7.2 secs | LR: 0.000251
I0522 06:16:09.513684 140402235246464 interactiveshell.py:2882] Step 3500 | Loss: 0.1598 | Spent: 6.8 secs | LR: 0.000251
I0522 06:16:16.348202 140402235246464 interactiveshell.py:2882] Step 3550 | Loss: 0.1466 | Spent: 6.8 secs | LR: 0.000250
I0522 06:16:23.208771 140402235246464 interactiveshell.py:2882] Step 3600 | Loss: 0.0893 | Spent: 6.9 secs | LR: 0.000249
I0522 06:16:30.050774 140402235246464 interactiveshell.py:2882] Step 3650 | Loss: 0.2871 | Spent: 6.8 secs | LR: 0.000249
I0522 06:16:36.931324 140402235246464 interactiveshell.py:2882] Step 3700 | Loss: 0.2039 | Spent: 6.9 secs | LR: 0.000248
I0522 06:16:43.807729 140402235246464 interactiveshell.py:2882] Step 3750 | Loss: 0.2324 | Spent: 6.9 secs | LR: 0.000248
I0522 06:16:51.137150 140402235246464 interactiveshell.py:2882] Step 3800 | Loss: 0.2798 | Spent: 7.3 secs | LR: 0.000247
I0522 06:16:58.222528 140402235246464 interactiveshell.py:2882] Step 3850 | Loss: 0.2471 | Spent: 7.1 secs | LR: 0.000246
I0522 06:17:05.081126 140402235246464 interactiveshell.py:2882] Step 3900 | Loss: 0.1424 | Spent: 6.9 secs | LR: 0.000246
Reading ../data/test.txt
I0522 06:18:52.502174 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.899
I0522 06:18:52.503273 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.899
Reading ../data/train.txt
I0522 06:19:05.657290 140402235246464 interactiveshell.py:2882] Step 3950 | Loss: 0.1101 | Spent: 120.6 secs | LR: 0.000245
I0522 06:19:12.581919 140402235246464 interactiveshell.py:2882] Step 4000 | Loss: 0.0737 | Spent: 6.9 secs | LR: 0.000244
I0522 06:19:19.472924 140402235246464 interactiveshell.py:2882] Step 4050 | Loss: 0.0432 | Spent: 6.9 secs | LR: 0.000244
I0522 06:19:26.508778 140402235246464 interactiveshell.py:2882] Step 4100 | Loss: 0.1020 | Spent: 7.0 secs | LR: 0.000243
I0522 06:19:33.906467 140402235246464 interactiveshell.py:2882] Step 4150 | Loss: 0.2175 | Spent: 7.4 secs | LR: 0.000242
I0522 06:19:40.798804 140402235246464 interactiveshell.py:2882] Step 4200 | Loss: 0.1585 | Spent: 6.9 secs | LR: 0.000242
I0522 06:19:47.653923 140402235246464 interactiveshell.py:2882] Step 4250 | Loss: 0.3178 | Spent: 6.9 secs | LR: 0.000241
I0522 06:19:54.474263 140402235246464 interactiveshell.py:2882] Step 4300 | Loss: 0.1328 | Spent: 6.8 secs | LR: 0.000241
I0522 06:20:01.261777 140402235246464 interactiveshell.py:2882] Step 4350 | Loss: 0.1766 | Spent: 6.8 secs | LR: 0.000240
I0522 06:20:08.052181 140402235246464 interactiveshell.py:2882] Step 4400 | Loss: 0.2023 | Spent: 6.8 secs | LR: 0.000239
I0522 06:20:14.850749 140402235246464 interactiveshell.py:2882] Step 4450 | Loss: 0.1509 | Spent: 6.8 secs | LR: 0.000239
I0522 06:20:21.762190 140402235246464 interactiveshell.py:2882] Step 4500 | Loss: 0.1529 | Spent: 6.9 secs | LR: 0.000238
I0522 06:20:28.588221 140402235246464 interactiveshell.py:2882] Step 4550 | Loss: 0.1580 | Spent: 6.8 secs | LR: 0.000238
I0522 06:20:35.432693 140402235246464 interactiveshell.py:2882] Step 4600 | Loss: 0.1910 | Spent: 6.8 secs | LR: 0.000237
I0522 06:20:42.278493 140402235246464 interactiveshell.py:2882] Step 4650 | Loss: 0.3312 | Spent: 6.8 secs | LR: 0.000236
Reading ../data/test.txt
I0522 06:22:34.344583 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.907
I0522 06:22:34.345644 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.907
Reading ../data/train.txt
I0522 06:22:43.043739 140402235246464 interactiveshell.py:2882] Step 4700 | Loss: 0.1357 | Spent: 120.8 secs | LR: 0.000236
I0522 06:22:49.883993 140402235246464 interactiveshell.py:2882] Step 4750 | Loss: 0.2093 | Spent: 6.8 secs | LR: 0.000235
I0522 06:22:56.735162 140402235246464 interactiveshell.py:2882] Step 4800 | Loss: 0.0270 | Spent: 6.8 secs | LR: 0.000235
I0522 06:23:03.595981 140402235246464 interactiveshell.py:2882] Step 4850 | Loss: 0.1542 | Spent: 6.9 secs | LR: 0.000234
I0522 06:23:10.424228 140402235246464 interactiveshell.py:2882] Step 4900 | Loss: 0.2587 | Spent: 6.8 secs | LR: 0.000233
I0522 06:23:17.282383 140402235246464 interactiveshell.py:2882] Step 4950 | Loss: 0.0821 | Spent: 6.9 secs | LR: 0.000233
I0522 06:23:24.079723 140402235246464 interactiveshell.py:2882] Step 5000 | Loss: 0.0985 | Spent: 6.8 secs | LR: 0.000232
I0522 06:23:31.252486 140402235246464 interactiveshell.py:2882] Step 5050 | Loss: 0.3514 | Spent: 7.2 secs | LR: 0.000232
I0522 06:23:38.373137 140402235246464 interactiveshell.py:2882] Step 5100 | Loss: 0.1915 | Spent: 7.1 secs | LR: 0.000231
I0522 06:23:45.267100 140402235246464 interactiveshell.py:2882] Step 5150 | Loss: 0.1393 | Spent: 6.9 secs | LR: 0.000230
I0522 06:23:52.074108 140402235246464 interactiveshell.py:2882] Step 5200 | Loss: 0.2597 | Spent: 6.8 secs | LR: 0.000230
I0522 06:23:58.876715 140402235246464 interactiveshell.py:2882] Step 5250 | Loss: 0.3065 | Spent: 6.8 secs | LR: 0.000229
I0522 06:24:05.709539 140402235246464 interactiveshell.py:2882] Step 5300 | Loss: 0.0972 | Spent: 6.8 secs | LR: 0.000229
I0522 06:24:12.520468 140402235246464 interactiveshell.py:2882] Step 5350 | Loss: 0.3014 | Spent: 6.8 secs | LR: 0.000228
I0522 06:24:19.367798 140402235246464 interactiveshell.py:2882] Step 5400 | Loss: 0.0597 | Spent: 6.8 secs | LR: 0.000227
I0522 06:24:26.219223 140402235246464 interactiveshell.py:2882] Step 5450 | Loss: 0.2051 | Spent: 6.8 secs | LR: 0.000227
Reading ../data/test.txt
I0522 06:26:14.815190 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.894
I0522 06:26:14.816756 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.907
Reading ../data/train.txt
I0522 06:26:26.856562 140402235246464 interactiveshell.py:2882] Step 5500 | Loss: 0.3609 | Spent: 120.6 secs | LR: 0.000226
I0522 06:26:33.688094 140402235246464 interactiveshell.py:2882] Step 5550 | Loss: 0.2901 | Spent: 6.8 secs | LR: 0.000226
I0522 06:26:40.626075 140402235246464 interactiveshell.py:2882] Step 5600 | Loss: 0.0780 | Spent: 6.9 secs | LR: 0.000225
I0522 06:26:47.534514 140402235246464 interactiveshell.py:2882] Step 5650 | Loss: 0.1032 | Spent: 6.9 secs | LR: 0.000225
I0522 06:26:54.366519 140402235246464 interactiveshell.py:2882] Step 5700 | Loss: 0.1426 | Spent: 6.8 secs | LR: 0.000224
I0522 06:27:01.165078 140402235246464 interactiveshell.py:2882] Step 5750 | Loss: 0.2619 | Spent: 6.8 secs | LR: 0.000223
I0522 06:27:08.063143 140402235246464 interactiveshell.py:2882] Step 5800 | Loss: 0.0799 | Spent: 6.9 secs | LR: 0.000223
I0522 06:27:14.871080 140402235246464 interactiveshell.py:2882] Step 5850 | Loss: 0.2706 | Spent: 6.8 secs | LR: 0.000222
I0522 06:27:21.657176 140402235246464 interactiveshell.py:2882] Step 5900 | Loss: 0.0806 | Spent: 6.8 secs | LR: 0.000222
I0522 06:27:28.523087 140402235246464 interactiveshell.py:2882] Step 5950 | Loss: 0.2051 | Spent: 6.9 secs | LR: 0.000221
I0522 06:27:35.810413 140402235246464 interactiveshell.py:2882] Step 6000 | Loss: 0.2346 | Spent: 7.3 secs | LR: 0.000221
I0522 06:27:42.735581 140402235246464 interactiveshell.py:2882] Step 6050 | Loss: 0.2433 | Spent: 6.9 secs | LR: 0.000220
I0522 06:27:49.523740 140402235246464 interactiveshell.py:2882] Step 6100 | Loss: 0.0752 | Spent: 6.8 secs | LR: 0.000219
I0522 06:27:56.331896 140402235246464 interactiveshell.py:2882] Step 6150 | Loss: 0.1302 | Spent: 6.8 secs | LR: 0.000219
I0522 06:28:03.138722 140402235246464 interactiveshell.py:2882] Step 6200 | Loss: 0.2172 | Spent: 6.8 secs | LR: 0.000218
I0522 06:28:09.982548 140402235246464 interactiveshell.py:2882] Step 6250 | Loss: 0.0889 | Spent: 6.8 secs | LR: 0.000218
Reading ../data/test.txt
I0522 06:29:55.425150 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 06:29:55.426209 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.911
Reading ../data/train.txt
I0522 06:30:09.075692 140402235246464 interactiveshell.py:2882] Step 6300 | Loss: 0.1609 | Spent: 119.1 secs | LR: 0.000217
I0522 06:30:16.437227 140402235246464 interactiveshell.py:2882] Step 6350 | Loss: 0.0919 | Spent: 7.4 secs | LR: 0.000217
I0522 06:30:23.386647 140402235246464 interactiveshell.py:2882] Step 6400 | Loss: 0.1610 | Spent: 6.9 secs | LR: 0.000216
I0522 06:30:30.305055 140402235246464 interactiveshell.py:2882] Step 6450 | Loss: 0.1549 | Spent: 6.9 secs | LR: 0.000215
I0522 06:30:37.121585 140402235246464 interactiveshell.py:2882] Step 6500 | Loss: 0.1879 | Spent: 6.8 secs | LR: 0.000215
I0522 06:30:43.958240 140402235246464 interactiveshell.py:2882] Step 6550 | Loss: 0.1583 | Spent: 6.8 secs | LR: 0.000214
I0522 06:30:50.766497 140402235246464 interactiveshell.py:2882] Step 6600 | Loss: 0.3273 | Spent: 6.8 secs | LR: 0.000214
I0522 06:30:57.572255 140402235246464 interactiveshell.py:2882] Step 6650 | Loss: 0.0971 | Spent: 6.8 secs | LR: 0.000213
I0522 06:31:04.364712 140402235246464 interactiveshell.py:2882] Step 6700 | Loss: 0.1230 | Spent: 6.8 secs | LR: 0.000213
I0522 06:31:11.157059 140402235246464 interactiveshell.py:2882] Step 6750 | Loss: 0.1397 | Spent: 6.8 secs | LR: 0.000212
I0522 06:31:17.949904 140402235246464 interactiveshell.py:2882] Step 6800 | Loss: 0.1877 | Spent: 6.8 secs | LR: 0.000212
I0522 06:31:25.355891 140402235246464 interactiveshell.py:2882] Step 6850 | Loss: 0.1397 | Spent: 7.4 secs | LR: 0.000211
I0522 06:31:32.839322 140402235246464 interactiveshell.py:2882] Step 6900 | Loss: 0.0720 | Spent: 7.5 secs | LR: 0.000211
I0522 06:31:40.073173 140402235246464 interactiveshell.py:2882] Step 6950 | Loss: 0.2220 | Spent: 7.2 secs | LR: 0.000210
I0522 06:31:46.913880 140402235246464 interactiveshell.py:2882] Step 7000 | Loss: 0.3076 | Spent: 6.8 secs | LR: 0.000210
Reading ../data/test.txt
I0522 06:33:36.419980 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.906
I0522 06:33:36.421041 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.911
Reading ../data/train.txt
I0522 06:33:45.610302 140402235246464 interactiveshell.py:2882] Step 7050 | Loss: 0.1776 | Spent: 118.7 secs | LR: 0.000209
I0522 06:33:52.438507 140402235246464 interactiveshell.py:2882] Step 7100 | Loss: 0.0281 | Spent: 6.8 secs | LR: 0.000208
I0522 06:33:59.370507 140402235246464 interactiveshell.py:2882] Step 7150 | Loss: 0.0826 | Spent: 6.9 secs | LR: 0.000208
I0522 06:34:06.193259 140402235246464 interactiveshell.py:2882] Step 7200 | Loss: 0.0346 | Spent: 6.8 secs | LR: 0.000207
I0522 06:34:13.256726 140402235246464 interactiveshell.py:2882] Step 7250 | Loss: 0.2024 | Spent: 7.1 secs | LR: 0.000207
I0522 06:34:20.495766 140402235246464 interactiveshell.py:2882] Step 7300 | Loss: 0.2130 | Spent: 7.2 secs | LR: 0.000206
I0522 06:34:27.291733 140402235246464 interactiveshell.py:2882] Step 7350 | Loss: 0.0884 | Spent: 6.8 secs | LR: 0.000206
I0522 06:34:34.089663 140402235246464 interactiveshell.py:2882] Step 7400 | Loss: 0.1325 | Spent: 6.8 secs | LR: 0.000205
I0522 06:34:40.919588 140402235246464 interactiveshell.py:2882] Step 7450 | Loss: 0.0808 | Spent: 6.8 secs | LR: 0.000205
I0522 06:34:48.128254 140402235246464 interactiveshell.py:2882] Step 7500 | Loss: 0.0732 | Spent: 7.2 secs | LR: 0.000204
I0522 06:34:54.916465 140402235246464 interactiveshell.py:2882] Step 7550 | Loss: 0.1521 | Spent: 6.8 secs | LR: 0.000204
I0522 06:35:01.716008 140402235246464 interactiveshell.py:2882] Step 7600 | Loss: 0.2044 | Spent: 6.8 secs | LR: 0.000203
I0522 06:35:08.518825 140402235246464 interactiveshell.py:2882] Step 7650 | Loss: 0.0916 | Spent: 6.8 secs | LR: 0.000203
I0522 06:35:15.342252 140402235246464 interactiveshell.py:2882] Step 7700 | Loss: 0.1911 | Spent: 6.8 secs | LR: 0.000202
I0522 06:35:22.159777 140402235246464 interactiveshell.py:2882] Step 7750 | Loss: 0.2124 | Spent: 6.8 secs | LR: 0.000202
I0522 06:35:28.976779 140402235246464 interactiveshell.py:2882] Step 7800 | Loss: 0.0928 | Spent: 6.8 secs | LR: 0.000201
Reading ../data/test.txt
I0522 06:37:18.808607 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 06:37:18.809705 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.911
Reading ../data/train.txt
I0522 06:37:30.584346 140402235246464 interactiveshell.py:2882] Step 7850 | Loss: 0.1861 | Spent: 121.6 secs | LR: 0.000201
I0522 06:37:37.398737 140402235246464 interactiveshell.py:2882] Step 7900 | Loss: 0.1843 | Spent: 6.8 secs | LR: 0.000200
I0522 06:37:44.266260 140402235246464 interactiveshell.py:2882] Step 7950 | Loss: 0.2032 | Spent: 6.9 secs | LR: 0.000200
I0522 06:37:51.092474 140402235246464 interactiveshell.py:2882] Step 8000 | Loss: 0.0964 | Spent: 6.8 secs | LR: 0.000199
I0522 06:37:57.909184 140402235246464 interactiveshell.py:2882] Step 8050 | Loss: 0.1006 | Spent: 6.8 secs | LR: 0.000199
I0522 06:38:04.735361 140402235246464 interactiveshell.py:2882] Step 8100 | Loss: 0.3585 | Spent: 6.8 secs | LR: 0.000198
I0522 06:38:11.567587 140402235246464 interactiveshell.py:2882] Step 8150 | Loss: 0.2314 | Spent: 6.8 secs | LR: 0.000198
I0522 06:38:18.822740 140402235246464 interactiveshell.py:2882] Step 8200 | Loss: 0.1488 | Spent: 7.3 secs | LR: 0.000197
I0522 06:38:25.720664 140402235246464 interactiveshell.py:2882] Step 8250 | Loss: 0.1043 | Spent: 6.9 secs | LR: 0.000196
I0522 06:38:32.514693 140402235246464 interactiveshell.py:2882] Step 8300 | Loss: 0.0244 | Spent: 6.8 secs | LR: 0.000196
I0522 06:38:39.319234 140402235246464 interactiveshell.py:2882] Step 8350 | Loss: 0.1692 | Spent: 6.8 secs | LR: 0.000195
I0522 06:38:46.136708 140402235246464 interactiveshell.py:2882] Step 8400 | Loss: 0.1787 | Spent: 6.8 secs | LR: 0.000195
I0522 06:38:52.935997 140402235246464 interactiveshell.py:2882] Step 8450 | Loss: 0.2514 | Spent: 6.8 secs | LR: 0.000194
I0522 06:38:59.740799 140402235246464 interactiveshell.py:2882] Step 8500 | Loss: 0.2531 | Spent: 6.8 secs | LR: 0.000194
I0522 06:39:06.538610 140402235246464 interactiveshell.py:2882] Step 8550 | Loss: 0.0566 | Spent: 6.8 secs | LR: 0.000193
I0522 06:39:13.431423 140402235246464 interactiveshell.py:2882] Step 8600 | Loss: 0.0412 | Spent: 6.9 secs | LR: 0.000193
Reading ../data/test.txt
I0522 06:40:58.516073 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.912
I0522 06:40:58.517301 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.912
Reading ../data/train.txt
I0522 06:41:13.104801 140402235246464 interactiveshell.py:2882] Step 8650 | Loss: 0.2664 | Spent: 119.7 secs | LR: 0.000192
I0522 06:41:19.937966 140402235246464 interactiveshell.py:2882] Step 8700 | Loss: 0.1378 | Spent: 6.8 secs | LR: 0.000192
I0522 06:41:26.771762 140402235246464 interactiveshell.py:2882] Step 8750 | Loss: 0.0937 | Spent: 6.8 secs | LR: 0.000192
I0522 06:41:33.575318 140402235246464 interactiveshell.py:2882] Step 8800 | Loss: 0.1154 | Spent: 6.8 secs | LR: 0.000191
I0522 06:41:40.398856 140402235246464 interactiveshell.py:2882] Step 8850 | Loss: 0.1146 | Spent: 6.8 secs | LR: 0.000191
I0522 06:41:47.981111 140402235246464 interactiveshell.py:2882] Step 8900 | Loss: 0.2384 | Spent: 7.6 secs | LR: 0.000190
I0522 06:41:55.096221 140402235246464 interactiveshell.py:2882] Step 8950 | Loss: 0.0899 | Spent: 7.1 secs | LR: 0.000190
I0522 06:42:01.893331 140402235246464 interactiveshell.py:2882] Step 9000 | Loss: 0.1195 | Spent: 6.8 secs | LR: 0.000189
I0522 06:42:08.715598 140402235246464 interactiveshell.py:2882] Step 9050 | Loss: 0.2247 | Spent: 6.8 secs | LR: 0.000189
I0522 06:42:15.764101 140402235246464 interactiveshell.py:2882] Step 9100 | Loss: 0.4165 | Spent: 7.0 secs | LR: 0.000188
I0522 06:42:23.002729 140402235246464 interactiveshell.py:2882] Step 9150 | Loss: 0.1253 | Spent: 7.2 secs | LR: 0.000188
I0522 06:42:29.827812 140402235246464 interactiveshell.py:2882] Step 9200 | Loss: 0.1143 | Spent: 6.8 secs | LR: 0.000187
I0522 06:42:36.724458 140402235246464 interactiveshell.py:2882] Step 9250 | Loss: 0.1268 | Spent: 6.9 secs | LR: 0.000187
I0522 06:42:43.562764 140402235246464 interactiveshell.py:2882] Step 9300 | Loss: 0.1344 | Spent: 6.8 secs | LR: 0.000186
I0522 06:42:50.425292 140402235246464 interactiveshell.py:2882] Step 9350 | Loss: 0.0823 | Spent: 6.9 secs | LR: 0.000186
Reading ../data/test.txt
I0522 06:44:40.201174 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.914
I0522 06:44:40.202232 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 06:44:50.015078 140402235246464 interactiveshell.py:2882] Step 9400 | Loss: 0.1393 | Spent: 119.6 secs | LR: 0.000185
I0522 06:44:57.395823 140402235246464 interactiveshell.py:2882] Step 9450 | Loss: 0.0958 | Spent: 7.4 secs | LR: 0.000185
I0522 06:45:04.652217 140402235246464 interactiveshell.py:2882] Step 9500 | Loss: 0.1275 | Spent: 7.3 secs | LR: 0.000184
I0522 06:45:11.507627 140402235246464 interactiveshell.py:2882] Step 9550 | Loss: 0.1468 | Spent: 6.9 secs | LR: 0.000184
I0522 06:45:18.350517 140402235246464 interactiveshell.py:2882] Step 9600 | Loss: 0.0524 | Spent: 6.8 secs | LR: 0.000183
I0522 06:45:25.171213 140402235246464 interactiveshell.py:2882] Step 9650 | Loss: 0.0898 | Spent: 6.8 secs | LR: 0.000183
I0522 06:45:32.015284 140402235246464 interactiveshell.py:2882] Step 9700 | Loss: 0.1953 | Spent: 6.8 secs | LR: 0.000182
I0522 06:45:38.816232 140402235246464 interactiveshell.py:2882] Step 9750 | Loss: 0.3519 | Spent: 6.8 secs | LR: 0.000182
I0522 06:45:45.636259 140402235246464 interactiveshell.py:2882] Step 9800 | Loss: 0.0196 | Spent: 6.8 secs | LR: 0.000181
I0522 06:45:52.470897 140402235246464 interactiveshell.py:2882] Step 9850 | Loss: 0.0404 | Spent: 6.8 secs | LR: 0.000181
I0522 06:45:59.300484 140402235246464 interactiveshell.py:2882] Step 9900 | Loss: 0.0973 | Spent: 6.8 secs | LR: 0.000181
I0522 06:46:06.199066 140402235246464 interactiveshell.py:2882] Step 9950 | Loss: 0.1482 | Spent: 6.9 secs | LR: 0.000180
I0522 06:46:13.005768 140402235246464 interactiveshell.py:2882] Step 10000 | Loss: 0.0315 | Spent: 6.8 secs | LR: 0.000180
I0522 06:46:20.291217 140402235246464 interactiveshell.py:2882] Step 10050 | Loss: 0.1192 | Spent: 7.3 secs | LR: 0.000179
I0522 06:46:27.383086 140402235246464 interactiveshell.py:2882] Step 10100 | Loss: 0.1727 | Spent: 7.1 secs | LR: 0.000179
I0522 06:46:34.283797 140402235246464 interactiveshell.py:2882] Step 10150 | Loss: 0.1478 | Spent: 6.9 secs | LR: 0.000178
Reading ../data/test.txt
I0522 06:48:22.993065 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 06:48:22.994109 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 06:48:35.229728 140402235246464 interactiveshell.py:2882] Step 10200 | Loss: 0.0559 | Spent: 120.9 secs | LR: 0.000178
I0522 06:48:42.147136 140402235246464 interactiveshell.py:2882] Step 10250 | Loss: 0.0269 | Spent: 6.9 secs | LR: 0.000177
I0522 06:48:49.052151 140402235246464 interactiveshell.py:2882] Step 10300 | Loss: 0.1323 | Spent: 6.9 secs | LR: 0.000177
I0522 06:48:56.046769 140402235246464 interactiveshell.py:2882] Step 10350 | Loss: 0.1299 | Spent: 7.0 secs | LR: 0.000176
I0522 06:49:03.381515 140402235246464 interactiveshell.py:2882] Step 10400 | Loss: 0.2252 | Spent: 7.3 secs | LR: 0.000176
I0522 06:49:10.237106 140402235246464 interactiveshell.py:2882] Step 10450 | Loss: 0.1070 | Spent: 6.9 secs | LR: 0.000176
I0522 06:49:17.062068 140402235246464 interactiveshell.py:2882] Step 10500 | Loss: 0.0216 | Spent: 6.8 secs | LR: 0.000175
I0522 06:49:23.858305 140402235246464 interactiveshell.py:2882] Step 10550 | Loss: 0.1752 | Spent: 6.8 secs | LR: 0.000175
I0522 06:49:30.671059 140402235246464 interactiveshell.py:2882] Step 10600 | Loss: 0.0909 | Spent: 6.8 secs | LR: 0.000174
I0522 06:49:37.487877 140402235246464 interactiveshell.py:2882] Step 10650 | Loss: 0.1396 | Spent: 6.8 secs | LR: 0.000174
I0522 06:49:44.384220 140402235246464 interactiveshell.py:2882] Step 10700 | Loss: 0.2350 | Spent: 6.9 secs | LR: 0.000173
I0522 06:49:51.207871 140402235246464 interactiveshell.py:2882] Step 10750 | Loss: 0.1068 | Spent: 6.8 secs | LR: 0.000173
I0522 06:49:58.170338 140402235246464 interactiveshell.py:2882] Step 10800 | Loss: 0.1371 | Spent: 7.0 secs | LR: 0.000172
I0522 06:50:05.357277 140402235246464 interactiveshell.py:2882] Step 10850 | Loss: 0.0208 | Spent: 7.2 secs | LR: 0.000172
I0522 06:50:12.176762 140402235246464 interactiveshell.py:2882] Step 10900 | Loss: 0.2614 | Spent: 6.8 secs | LR: 0.000172
Reading ../data/test.txt
I0522 06:52:05.538911 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.912
I0522 06:52:05.540140 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 06:52:14.714221 140402235246464 interactiveshell.py:2882] Step 10950 | Loss: 0.0496 | Spent: 122.5 secs | LR: 0.000171
I0522 06:52:21.654837 140402235246464 interactiveshell.py:2882] Step 11000 | Loss: 0.0093 | Spent: 6.9 secs | LR: 0.000171
I0522 06:52:28.552247 140402235246464 interactiveshell.py:2882] Step 11050 | Loss: 0.0469 | Spent: 6.9 secs | LR: 0.000170
I0522 06:52:35.514947 140402235246464 interactiveshell.py:2882] Step 11100 | Loss: 0.0942 | Spent: 7.0 secs | LR: 0.000170
I0522 06:52:42.416379 140402235246464 interactiveshell.py:2882] Step 11150 | Loss: 0.1271 | Spent: 6.9 secs | LR: 0.000169
I0522 06:52:49.327667 140402235246464 interactiveshell.py:2882] Step 11200 | Loss: 0.1166 | Spent: 6.9 secs | LR: 0.000169
I0522 06:52:56.247568 140402235246464 interactiveshell.py:2882] Step 11250 | Loss: 0.0428 | Spent: 6.9 secs | LR: 0.000168
I0522 06:53:03.579740 140402235246464 interactiveshell.py:2882] Step 11300 | Loss: 0.2368 | Spent: 7.3 secs | LR: 0.000168
I0522 06:53:10.526969 140402235246464 interactiveshell.py:2882] Step 11350 | Loss: 0.1118 | Spent: 6.9 secs | LR: 0.000168
I0522 06:53:17.473959 140402235246464 interactiveshell.py:2882] Step 11400 | Loss: 0.1002 | Spent: 6.9 secs | LR: 0.000167
I0522 06:53:24.311269 140402235246464 interactiveshell.py:2882] Step 11450 | Loss: 0.3010 | Spent: 6.8 secs | LR: 0.000167
I0522 06:53:31.191860 140402235246464 interactiveshell.py:2882] Step 11500 | Loss: 0.0271 | Spent: 6.9 secs | LR: 0.000166
I0522 06:53:38.038724 140402235246464 interactiveshell.py:2882] Step 11550 | Loss: 0.1126 | Spent: 6.8 secs | LR: 0.000166
I0522 06:53:44.920167 140402235246464 interactiveshell.py:2882] Step 11600 | Loss: 0.0653 | Spent: 6.9 secs | LR: 0.000165
I0522 06:53:51.799844 140402235246464 interactiveshell.py:2882] Step 11650 | Loss: 0.0888 | Spent: 6.9 secs | LR: 0.000165
I0522 06:53:58.694617 140402235246464 interactiveshell.py:2882] Step 11700 | Loss: 0.0803 | Spent: 6.9 secs | LR: 0.000165
Reading ../data/test.txt
I0522 06:55:49.834080 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.908
I0522 06:55:49.835189 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 06:56:00.270177 140402235246464 interactiveshell.py:2882] Step 11750 | Loss: 0.0798 | Spent: 121.6 secs | LR: 0.000164
I0522 06:56:07.170731 140402235246464 interactiveshell.py:2882] Step 11800 | Loss: 0.0157 | Spent: 6.9 secs | LR: 0.000164
I0522 06:56:14.052650 140402235246464 interactiveshell.py:2882] Step 11850 | Loss: 0.0051 | Spent: 6.9 secs | LR: 0.000163
I0522 06:56:20.976266 140402235246464 interactiveshell.py:2882] Step 11900 | Loss: 0.0666 | Spent: 6.9 secs | LR: 0.000163
I0522 06:56:27.862548 140402235246464 interactiveshell.py:2882] Step 11950 | Loss: 0.2004 | Spent: 6.9 secs | LR: 0.000163
I0522 06:56:34.730130 140402235246464 interactiveshell.py:2882] Step 12000 | Loss: 0.0191 | Spent: 6.9 secs | LR: 0.000162
I0522 06:56:41.598624 140402235246464 interactiveshell.py:2882] Step 12050 | Loss: 0.0272 | Spent: 6.9 secs | LR: 0.000162
I0522 06:56:48.507043 140402235246464 interactiveshell.py:2882] Step 12100 | Loss: 0.1289 | Spent: 6.9 secs | LR: 0.000161
I0522 06:56:55.434034 140402235246464 interactiveshell.py:2882] Step 12150 | Loss: 0.0919 | Spent: 6.9 secs | LR: 0.000161
I0522 06:57:02.689915 140402235246464 interactiveshell.py:2882] Step 12200 | Loss: 0.0888 | Spent: 7.3 secs | LR: 0.000160
I0522 06:57:09.766734 140402235246464 interactiveshell.py:2882] Step 12250 | Loss: 0.1053 | Spent: 7.1 secs | LR: 0.000160
I0522 06:57:17.112355 140402235246464 interactiveshell.py:2882] Step 12300 | Loss: 0.1443 | Spent: 7.3 secs | LR: 0.000160
I0522 06:57:24.546762 140402235246464 interactiveshell.py:2882] Step 12350 | Loss: 0.0547 | Spent: 7.4 secs | LR: 0.000159
I0522 06:57:31.412421 140402235246464 interactiveshell.py:2882] Step 12400 | Loss: 0.0364 | Spent: 6.9 secs | LR: 0.000159
I0522 06:57:38.275461 140402235246464 interactiveshell.py:2882] Step 12450 | Loss: 0.0845 | Spent: 6.9 secs | LR: 0.000158
I0522 06:57:45.144725 140402235246464 interactiveshell.py:2882] Step 12500 | Loss: 0.0599 | Spent: 6.9 secs | LR: 0.000158
Reading ../data/test.txt
I0522 06:59:32.989840 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.901
I0522 06:59:32.990915 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 06:59:46.708635 140402235246464 interactiveshell.py:2882] Step 12550 | Loss: 0.0490 | Spent: 121.6 secs | LR: 0.000158
I0522 06:59:53.685749 140402235246464 interactiveshell.py:2882] Step 12600 | Loss: 0.0049 | Spent: 7.0 secs | LR: 0.000157
I0522 07:00:00.634751 140402235246464 interactiveshell.py:2882] Step 12650 | Loss: 0.0143 | Spent: 6.9 secs | LR: 0.000157
I0522 07:00:07.523361 140402235246464 interactiveshell.py:2882] Step 12700 | Loss: 0.0056 | Spent: 6.9 secs | LR: 0.000156
I0522 07:00:14.798776 140402235246464 interactiveshell.py:2882] Step 12750 | Loss: 0.0139 | Spent: 7.3 secs | LR: 0.000156
I0522 07:00:21.681604 140402235246464 interactiveshell.py:2882] Step 12800 | Loss: 0.0812 | Spent: 6.9 secs | LR: 0.000156
I0522 07:00:28.657087 140402235246464 interactiveshell.py:2882] Step 12850 | Loss: 0.0169 | Spent: 7.0 secs | LR: 0.000155
I0522 07:00:35.595755 140402235246464 interactiveshell.py:2882] Step 12900 | Loss: 0.0726 | Spent: 6.9 secs | LR: 0.000155
I0522 07:00:42.422729 140402235246464 interactiveshell.py:2882] Step 12950 | Loss: 0.1005 | Spent: 6.8 secs | LR: 0.000154
I0522 07:00:49.281053 140402235246464 interactiveshell.py:2882] Step 13000 | Loss: 0.0119 | Spent: 6.9 secs | LR: 0.000154
I0522 07:00:56.156552 140402235246464 interactiveshell.py:2882] Step 13050 | Loss: 0.0195 | Spent: 6.9 secs | LR: 0.000154
I0522 07:01:03.381594 140402235246464 interactiveshell.py:2882] Step 13100 | Loss: 0.0538 | Spent: 7.2 secs | LR: 0.000153
I0522 07:01:10.511772 140402235246464 interactiveshell.py:2882] Step 13150 | Loss: 0.0229 | Spent: 7.1 secs | LR: 0.000153
I0522 07:01:17.396745 140402235246464 interactiveshell.py:2882] Step 13200 | Loss: 0.2334 | Spent: 6.9 secs | LR: 0.000152
I0522 07:01:24.277471 140402235246464 interactiveshell.py:2882] Step 13250 | Loss: 0.0323 | Spent: 6.9 secs | LR: 0.000152
Reading ../data/test.txt
I0522 07:03:17.369732 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.912
I0522 07:03:17.370857 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:03:25.790278 140402235246464 interactiveshell.py:2882] Step 13300 | Loss: 0.1767 | Spent: 121.5 secs | LR: 0.000152
I0522 07:03:32.688278 140402235246464 interactiveshell.py:2882] Step 13350 | Loss: 0.0332 | Spent: 6.9 secs | LR: 0.000151
I0522 07:03:39.699205 140402235246464 interactiveshell.py:2882] Step 13400 | Loss: 0.0257 | Spent: 7.0 secs | LR: 0.000151
I0522 07:03:47.088005 140402235246464 interactiveshell.py:2882] Step 13450 | Loss: 0.0020 | Spent: 7.4 secs | LR: 0.000150
I0522 07:03:54.123991 140402235246464 interactiveshell.py:2882] Step 13500 | Loss: 0.0882 | Spent: 7.0 secs | LR: 0.000150
I0522 07:04:01.020809 140402235246464 interactiveshell.py:2882] Step 13550 | Loss: 0.0852 | Spent: 6.9 secs | LR: 0.000150
I0522 07:04:07.876357 140402235246464 interactiveshell.py:2882] Step 13600 | Loss: 0.0127 | Spent: 6.9 secs | LR: 0.000149
I0522 07:04:14.833215 140402235246464 interactiveshell.py:2882] Step 13650 | Loss: 0.0077 | Spent: 7.0 secs | LR: 0.000149
I0522 07:04:21.663035 140402235246464 interactiveshell.py:2882] Step 13700 | Loss: 0.0095 | Spent: 6.8 secs | LR: 0.000149
I0522 07:04:28.522459 140402235246464 interactiveshell.py:2882] Step 13750 | Loss: 0.0333 | Spent: 6.9 secs | LR: 0.000148
I0522 07:04:35.424968 140402235246464 interactiveshell.py:2882] Step 13800 | Loss: 0.0361 | Spent: 6.9 secs | LR: 0.000148
I0522 07:04:42.282257 140402235246464 interactiveshell.py:2882] Step 13850 | Loss: 0.1067 | Spent: 6.9 secs | LR: 0.000147
I0522 07:04:49.210001 140402235246464 interactiveshell.py:2882] Step 13900 | Loss: 0.0354 | Spent: 6.9 secs | LR: 0.000147
I0522 07:04:56.123201 140402235246464 interactiveshell.py:2882] Step 13950 | Loss: 0.2222 | Spent: 6.9 secs | LR: 0.000147
I0522 07:05:03.285357 140402235246464 interactiveshell.py:2882] Step 14000 | Loss: 0.0662 | Spent: 7.2 secs | LR: 0.000146
I0522 07:05:10.562179 140402235246464 interactiveshell.py:2882] Step 14050 | Loss: 0.0429 | Spent: 7.3 secs | LR: 0.000146
Reading ../data/test.txt
I0522 07:07:01.339755 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.912
I0522 07:07:01.340855 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:07:12.286975 140402235246464 interactiveshell.py:2882] Step 14100 | Loss: 0.0102 | Spent: 121.7 secs | LR: 0.000146
I0522 07:07:19.198739 140402235246464 interactiveshell.py:2882] Step 14150 | Loss: 0.1038 | Spent: 6.9 secs | LR: 0.000145
I0522 07:07:26.140832 140402235246464 interactiveshell.py:2882] Step 14200 | Loss: 0.0134 | Spent: 6.9 secs | LR: 0.000145
I0522 07:07:33.029822 140402235246464 interactiveshell.py:2882] Step 14250 | Loss: 0.0156 | Spent: 6.9 secs | LR: 0.000144
I0522 07:07:40.688326 140402235246464 interactiveshell.py:2882] Step 14300 | Loss: 0.0310 | Spent: 7.7 secs | LR: 0.000144
I0522 07:07:48.159540 140402235246464 interactiveshell.py:2882] Step 14350 | Loss: 0.0109 | Spent: 7.5 secs | LR: 0.000144
I0522 07:07:55.252074 140402235246464 interactiveshell.py:2882] Step 14400 | Loss: 0.1159 | Spent: 7.1 secs | LR: 0.000143
I0522 07:08:02.115872 140402235246464 interactiveshell.py:2882] Step 14450 | Loss: 0.0864 | Spent: 6.9 secs | LR: 0.000143
I0522 07:08:08.999214 140402235246464 interactiveshell.py:2882] Step 14500 | Loss: 0.0228 | Spent: 6.9 secs | LR: 0.000143
I0522 07:08:15.845644 140402235246464 interactiveshell.py:2882] Step 14550 | Loss: 0.1447 | Spent: 6.8 secs | LR: 0.000142
I0522 07:08:22.714199 140402235246464 interactiveshell.py:2882] Step 14600 | Loss: 0.0087 | Spent: 6.9 secs | LR: 0.000142
I0522 07:08:29.567389 140402235246464 interactiveshell.py:2882] Step 14650 | Loss: 0.0124 | Spent: 6.9 secs | LR: 0.000142
I0522 07:08:36.446705 140402235246464 interactiveshell.py:2882] Step 14700 | Loss: 0.0356 | Spent: 6.9 secs | LR: 0.000141
I0522 07:08:43.349556 140402235246464 interactiveshell.py:2882] Step 14750 | Loss: 0.0101 | Spent: 6.9 secs | LR: 0.000141
I0522 07:08:50.254608 140402235246464 interactiveshell.py:2882] Step 14800 | Loss: 0.0340 | Spent: 6.9 secs | LR: 0.000140
I0522 07:08:57.175213 140402235246464 interactiveshell.py:2882] Step 14850 | Loss: 0.1308 | Spent: 6.9 secs | LR: 0.000140
Reading ../data/test.txt
I0522 07:10:46.159139 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.900
I0522 07:10:46.160284 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:10:59.589663 140402235246464 interactiveshell.py:2882] Step 14900 | Loss: 0.0113 | Spent: 122.4 secs | LR: 0.000140
I0522 07:11:06.494262 140402235246464 interactiveshell.py:2882] Step 14950 | Loss: 0.0562 | Spent: 6.9 secs | LR: 0.000139
I0522 07:11:13.409771 140402235246464 interactiveshell.py:2882] Step 15000 | Loss: 0.0787 | Spent: 6.9 secs | LR: 0.000139
I0522 07:11:20.335127 140402235246464 interactiveshell.py:2882] Step 15050 | Loss: 0.0607 | Spent: 6.9 secs | LR: 0.000139
I0522 07:11:27.206620 140402235246464 interactiveshell.py:2882] Step 15100 | Loss: 0.0072 | Spent: 6.9 secs | LR: 0.000138
I0522 07:11:34.191968 140402235246464 interactiveshell.py:2882] Step 15150 | Loss: 0.0077 | Spent: 7.0 secs | LR: 0.000138
I0522 07:11:41.053220 140402235246464 interactiveshell.py:2882] Step 15200 | Loss: 0.0053 | Spent: 6.9 secs | LR: 0.000138
I0522 07:11:48.405081 140402235246464 interactiveshell.py:2882] Step 15250 | Loss: 0.0181 | Spent: 7.4 secs | LR: 0.000137
I0522 07:11:55.470633 140402235246464 interactiveshell.py:2882] Step 15300 | Loss: 0.0104 | Spent: 7.1 secs | LR: 0.000137
I0522 07:12:02.310763 140402235246464 interactiveshell.py:2882] Step 15350 | Loss: 0.0239 | Spent: 6.8 secs | LR: 0.000137
I0522 07:12:09.142316 140402235246464 interactiveshell.py:2882] Step 15400 | Loss: 0.0062 | Spent: 6.8 secs | LR: 0.000136
I0522 07:12:15.997697 140402235246464 interactiveshell.py:2882] Step 15450 | Loss: 0.0056 | Spent: 6.9 secs | LR: 0.000136
I0522 07:12:22.881638 140402235246464 interactiveshell.py:2882] Step 15500 | Loss: 0.0495 | Spent: 6.9 secs | LR: 0.000135
I0522 07:12:29.763161 140402235246464 interactiveshell.py:2882] Step 15550 | Loss: 0.1161 | Spent: 6.9 secs | LR: 0.000135
I0522 07:12:36.663003 140402235246464 interactiveshell.py:2882] Step 15600 | Loss: 0.1460 | Spent: 6.9 secs | LR: 0.000135
Reading ../data/test.txt
I0522 07:14:30.354933 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 07:14:30.356126 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:14:39.572585 140402235246464 interactiveshell.py:2882] Step 15650 | Loss: 0.0018 | Spent: 122.9 secs | LR: 0.000134
I0522 07:14:46.455155 140402235246464 interactiveshell.py:2882] Step 15700 | Loss: 0.0079 | Spent: 6.9 secs | LR: 0.000134
I0522 07:14:53.392563 140402235246464 interactiveshell.py:2882] Step 15750 | Loss: 0.0343 | Spent: 6.9 secs | LR: 0.000134
I0522 07:15:00.352054 140402235246464 interactiveshell.py:2882] Step 15800 | Loss: 0.0279 | Spent: 7.0 secs | LR: 0.000133
I0522 07:15:07.252303 140402235246464 interactiveshell.py:2882] Step 15850 | Loss: 0.0889 | Spent: 6.9 secs | LR: 0.000133
I0522 07:15:14.126775 140402235246464 interactiveshell.py:2882] Step 15900 | Loss: 0.0259 | Spent: 6.9 secs | LR: 0.000133
I0522 07:15:21.097755 140402235246464 interactiveshell.py:2882] Step 15950 | Loss: 0.0086 | Spent: 7.0 secs | LR: 0.000132
I0522 07:15:28.402236 140402235246464 interactiveshell.py:2882] Step 16000 | Loss: 0.1111 | Spent: 7.3 secs | LR: 0.000132
I0522 07:15:35.257214 140402235246464 interactiveshell.py:2882] Step 16050 | Loss: 0.0151 | Spent: 6.9 secs | LR: 0.000132
I0522 07:15:42.091645 140402235246464 interactiveshell.py:2882] Step 16100 | Loss: 0.0085 | Spent: 6.8 secs | LR: 0.000131
I0522 07:15:49.383778 140402235246464 interactiveshell.py:2882] Step 16150 | Loss: 0.0416 | Spent: 7.3 secs | LR: 0.000131
I0522 07:15:56.441231 140402235246464 interactiveshell.py:2882] Step 16200 | Loss: 0.0254 | Spent: 7.1 secs | LR: 0.000131
I0522 07:16:03.287670 140402235246464 interactiveshell.py:2882] Step 16250 | Loss: 0.0103 | Spent: 6.8 secs | LR: 0.000130
I0522 07:16:10.158223 140402235246464 interactiveshell.py:2882] Step 16300 | Loss: 0.0291 | Spent: 6.9 secs | LR: 0.000130
I0522 07:16:17.011714 140402235246464 interactiveshell.py:2882] Step 16350 | Loss: 0.0978 | Spent: 6.9 secs | LR: 0.000130
I0522 07:16:23.890296 140402235246464 interactiveshell.py:2882] Step 16400 | Loss: 0.0016 | Spent: 6.9 secs | LR: 0.000129
Reading ../data/test.txt
I0522 07:18:14.833407 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 07:18:14.834524 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:18:26.555531 140402235246464 interactiveshell.py:2882] Step 16450 | Loss: 0.0912 | Spent: 122.7 secs | LR: 0.000129
I0522 07:18:33.887727 140402235246464 interactiveshell.py:2882] Step 16500 | Loss: 0.0260 | Spent: 7.3 secs | LR: 0.000129
I0522 07:18:40.815937 140402235246464 interactiveshell.py:2882] Step 16550 | Loss: 0.0138 | Spent: 6.9 secs | LR: 0.000128
I0522 07:18:47.728306 140402235246464 interactiveshell.py:2882] Step 16600 | Loss: 0.2379 | Spent: 6.9 secs | LR: 0.000128
I0522 07:18:54.593090 140402235246464 interactiveshell.py:2882] Step 16650 | Loss: 0.0488 | Spent: 6.9 secs | LR: 0.000128
I0522 07:19:01.600358 140402235246464 interactiveshell.py:2882] Step 16700 | Loss: 0.0032 | Spent: 7.0 secs | LR: 0.000127
I0522 07:19:08.476463 140402235246464 interactiveshell.py:2882] Step 16750 | Loss: 0.0092 | Spent: 6.9 secs | LR: 0.000127
I0522 07:19:15.352861 140402235246464 interactiveshell.py:2882] Step 16800 | Loss: 0.1586 | Spent: 6.9 secs | LR: 0.000127
I0522 07:19:22.193186 140402235246464 interactiveshell.py:2882] Step 16850 | Loss: 0.0152 | Spent: 6.8 secs | LR: 0.000126
I0522 07:19:29.038640 140402235246464 interactiveshell.py:2882] Step 16900 | Loss: 0.1183 | Spent: 6.8 secs | LR: 0.000126
I0522 07:19:35.911254 140402235246464 interactiveshell.py:2882] Step 16950 | Loss: 0.0600 | Spent: 6.9 secs | LR: 0.000126
I0522 07:19:42.770925 140402235246464 interactiveshell.py:2882] Step 17000 | Loss: 0.0462 | Spent: 6.9 secs | LR: 0.000125
I0522 07:19:50.037309 140402235246464 interactiveshell.py:2882] Step 17050 | Loss: 0.0269 | Spent: 7.3 secs | LR: 0.000125
I0522 07:19:57.150326 140402235246464 interactiveshell.py:2882] Step 17100 | Loss: 0.0018 | Spent: 7.1 secs | LR: 0.000125
I0522 07:20:04.087410 140402235246464 interactiveshell.py:2882] Step 17150 | Loss: 0.0318 | Spent: 6.9 secs | LR: 0.000124
I0522 07:20:10.971825 140402235246464 interactiveshell.py:2882] Step 17200 | Loss: 0.0335 | Spent: 6.9 secs | LR: 0.000124
Reading ../data/test.txt
I0522 07:21:59.206997 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.907
I0522 07:21:59.208075 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:22:13.156580 140402235246464 interactiveshell.py:2882] Step 17250 | Loss: 0.0218 | Spent: 122.2 secs | LR: 0.000124
I0522 07:22:20.069340 140402235246464 interactiveshell.py:2882] Step 17300 | Loss: 0.0116 | Spent: 6.9 secs | LR: 0.000124
I0522 07:22:27.168929 140402235246464 interactiveshell.py:2882] Step 17350 | Loss: 0.0197 | Spent: 7.1 secs | LR: 0.000123
I0522 07:22:34.567496 140402235246464 interactiveshell.py:2882] Step 17400 | Loss: 0.0051 | Spent: 7.4 secs | LR: 0.000123
I0522 07:22:41.475265 140402235246464 interactiveshell.py:2882] Step 17450 | Loss: 0.1205 | Spent: 6.9 secs | LR: 0.000123
I0522 07:22:48.449386 140402235246464 interactiveshell.py:2882] Step 17500 | Loss: 0.0133 | Spent: 7.0 secs | LR: 0.000122
I0522 07:22:55.291772 140402235246464 interactiveshell.py:2882] Step 17550 | Loss: 0.0591 | Spent: 6.8 secs | LR: 0.000122
I0522 07:23:02.171685 140402235246464 interactiveshell.py:2882] Step 17600 | Loss: 0.0046 | Spent: 6.9 secs | LR: 0.000122
I0522 07:23:09.510268 140402235246464 interactiveshell.py:2882] Step 17650 | Loss: 0.0146 | Spent: 7.3 secs | LR: 0.000121
I0522 07:23:16.956137 140402235246464 interactiveshell.py:2882] Step 17700 | Loss: 0.1568 | Spent: 7.4 secs | LR: 0.000121
I0522 07:23:23.833385 140402235246464 interactiveshell.py:2882] Step 17750 | Loss: 0.0730 | Spent: 6.9 secs | LR: 0.000121
I0522 07:23:30.719892 140402235246464 interactiveshell.py:2882] Step 17800 | Loss: 0.0022 | Spent: 6.9 secs | LR: 0.000120
I0522 07:23:37.619257 140402235246464 interactiveshell.py:2882] Step 17850 | Loss: 0.0042 | Spent: 6.9 secs | LR: 0.000120
I0522 07:23:44.550513 140402235246464 interactiveshell.py:2882] Step 17900 | Loss: 0.0243 | Spent: 6.9 secs | LR: 0.000120
I0522 07:23:51.908392 140402235246464 interactiveshell.py:2882] Step 17950 | Loss: 0.0173 | Spent: 7.4 secs | LR: 0.000119
Reading ../data/test.txt
I0522 07:25:44.755168 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.900
I0522 07:25:44.756531 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:25:54.350785 140402235246464 interactiveshell.py:2882] Step 18000 | Loss: 0.0214 | Spent: 122.4 secs | LR: 0.000119
I0522 07:26:01.259637 140402235246464 interactiveshell.py:2882] Step 18050 | Loss: 0.0171 | Spent: 6.9 secs | LR: 0.000119
I0522 07:26:08.170972 140402235246464 interactiveshell.py:2882] Step 18100 | Loss: 0.0020 | Spent: 6.9 secs | LR: 0.000119
I0522 07:26:15.117717 140402235246464 interactiveshell.py:2882] Step 18150 | Loss: 0.0290 | Spent: 6.9 secs | LR: 0.000118
I0522 07:26:22.030156 140402235246464 interactiveshell.py:2882] Step 18200 | Loss: 0.0384 | Spent: 6.9 secs | LR: 0.000118
I0522 07:26:29.129023 140402235246464 interactiveshell.py:2882] Step 18250 | Loss: 0.1844 | Spent: 7.1 secs | LR: 0.000118
I0522 07:26:36.574708 140402235246464 interactiveshell.py:2882] Step 18300 | Loss: 0.1686 | Spent: 7.4 secs | LR: 0.000117
I0522 07:26:43.485729 140402235246464 interactiveshell.py:2882] Step 18350 | Loss: 0.0098 | Spent: 6.9 secs | LR: 0.000117
I0522 07:26:50.388989 140402235246464 interactiveshell.py:2882] Step 18400 | Loss: 0.0046 | Spent: 6.9 secs | LR: 0.000117
I0522 07:26:57.274117 140402235246464 interactiveshell.py:2882] Step 18450 | Loss: 0.0078 | Spent: 6.9 secs | LR: 0.000116
I0522 07:27:04.167367 140402235246464 interactiveshell.py:2882] Step 18500 | Loss: 0.0036 | Spent: 6.9 secs | LR: 0.000116
I0522 07:27:11.007894 140402235246464 interactiveshell.py:2882] Step 18550 | Loss: 0.0194 | Spent: 6.8 secs | LR: 0.000116
I0522 07:27:17.909585 140402235246464 interactiveshell.py:2882] Step 18600 | Loss: 0.0020 | Spent: 6.9 secs | LR: 0.000116
I0522 07:27:24.797002 140402235246464 interactiveshell.py:2882] Step 18650 | Loss: 0.0513 | Spent: 6.9 secs | LR: 0.000115
I0522 07:27:31.681270 140402235246464 interactiveshell.py:2882] Step 18700 | Loss: 0.0844 | Spent: 6.9 secs | LR: 0.000115
I0522 07:27:38.584720 140402235246464 interactiveshell.py:2882] Step 18750 | Loss: 0.0057 | Spent: 6.9 secs | LR: 0.000115
Reading ../data/test.txt
I0522 07:29:30.605238 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.908
I0522 07:29:30.606385 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:29:42.636210 140402235246464 interactiveshell.py:2882] Step 18800 | Loss: 0.0051 | Spent: 124.1 secs | LR: 0.000114
I0522 07:29:49.569175 140402235246464 interactiveshell.py:2882] Step 18850 | Loss: 0.0466 | Spent: 6.9 secs | LR: 0.000114
I0522 07:29:56.515075 140402235246464 interactiveshell.py:2882] Step 18900 | Loss: 0.0730 | Spent: 6.9 secs | LR: 0.000114
I0522 07:30:03.436621 140402235246464 interactiveshell.py:2882] Step 18950 | Loss: 0.0275 | Spent: 6.9 secs | LR: 0.000113
I0522 07:30:10.365971 140402235246464 interactiveshell.py:2882] Step 19000 | Loss: 0.0088 | Spent: 6.9 secs | LR: 0.000113
I0522 07:30:17.280979 140402235246464 interactiveshell.py:2882] Step 19050 | Loss: 0.0380 | Spent: 6.9 secs | LR: 0.000113
I0522 07:30:24.352839 140402235246464 interactiveshell.py:2882] Step 19100 | Loss: 0.0106 | Spent: 7.1 secs | LR: 0.000113
I0522 07:30:31.521257 140402235246464 interactiveshell.py:2882] Step 19150 | Loss: 0.0115 | Spent: 7.2 secs | LR: 0.000112
I0522 07:30:38.774805 140402235246464 interactiveshell.py:2882] Step 19200 | Loss: 0.0055 | Spent: 7.3 secs | LR: 0.000112
I0522 07:30:46.105624 140402235246464 interactiveshell.py:2882] Step 19250 | Loss: 0.0784 | Spent: 7.3 secs | LR: 0.000112
I0522 07:30:52.992941 140402235246464 interactiveshell.py:2882] Step 19300 | Loss: 0.0072 | Spent: 6.9 secs | LR: 0.000111
I0522 07:30:59.916065 140402235246464 interactiveshell.py:2882] Step 19350 | Loss: 0.0909 | Spent: 6.9 secs | LR: 0.000111
I0522 07:31:06.818567 140402235246464 interactiveshell.py:2882] Step 19400 | Loss: 0.0190 | Spent: 6.9 secs | LR: 0.000111
I0522 07:31:13.719258 140402235246464 interactiveshell.py:2882] Step 19450 | Loss: 0.0020 | Spent: 6.9 secs | LR: 0.000111
I0522 07:31:20.630391 140402235246464 interactiveshell.py:2882] Step 19500 | Loss: 0.1288 | Spent: 6.9 secs | LR: 0.000110
Reading ../data/test.txt
I0522 07:33:15.641108 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.908
I0522 07:33:15.642217 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:33:23.530832 140402235246464 interactiveshell.py:2882] Step 19550 | Loss: 0.0098 | Spent: 122.9 secs | LR: 0.000110
I0522 07:33:31.039191 140402235246464 interactiveshell.py:2882] Step 19600 | Loss: 0.0167 | Spent: 7.5 secs | LR: 0.000110
I0522 07:33:38.498613 140402235246464 interactiveshell.py:2882] Step 19650 | Loss: 0.0421 | Spent: 7.5 secs | LR: 0.000109
I0522 07:33:45.424473 140402235246464 interactiveshell.py:2882] Step 19700 | Loss: 0.0993 | Spent: 6.9 secs | LR: 0.000109
I0522 07:33:52.316243 140402235246464 interactiveshell.py:2882] Step 19750 | Loss: 0.0470 | Spent: 6.9 secs | LR: 0.000109
I0522 07:33:59.233531 140402235246464 interactiveshell.py:2882] Step 19800 | Loss: 0.0198 | Spent: 6.9 secs | LR: 0.000109
I0522 07:34:06.111073 140402235246464 interactiveshell.py:2882] Step 19850 | Loss: 0.1345 | Spent: 6.9 secs | LR: 0.000108
I0522 07:34:13.134121 140402235246464 interactiveshell.py:2882] Step 19900 | Loss: 0.0096 | Spent: 7.0 secs | LR: 0.000108
I0522 07:34:20.028144 140402235246464 interactiveshell.py:2882] Step 19950 | Loss: 0.0170 | Spent: 6.9 secs | LR: 0.000108
I0522 07:34:26.904240 140402235246464 interactiveshell.py:2882] Step 20000 | Loss: 0.0071 | Spent: 6.9 secs | LR: 0.000108
I0522 07:34:34.116727 140402235246464 interactiveshell.py:2882] Step 20050 | Loss: 0.0388 | Spent: 7.2 secs | LR: 0.000107
I0522 07:34:41.293098 140402235246464 interactiveshell.py:2882] Step 20100 | Loss: 0.1663 | Spent: 7.2 secs | LR: 0.000107
I0522 07:34:48.202761 140402235246464 interactiveshell.py:2882] Step 20150 | Loss: 0.0220 | Spent: 6.9 secs | LR: 0.000107
I0522 07:34:55.123602 140402235246464 interactiveshell.py:2882] Step 20200 | Loss: 0.0412 | Spent: 6.9 secs | LR: 0.000106
I0522 07:35:02.058805 140402235246464 interactiveshell.py:2882] Step 20250 | Loss: 0.0139 | Spent: 6.9 secs | LR: 0.000106
I0522 07:35:08.957621 140402235246464 interactiveshell.py:2882] Step 20300 | Loss: 0.0151 | Spent: 6.9 secs | LR: 0.000106
Reading ../data/test.txt
I0522 07:37:01.930261 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 07:37:01.931344 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:37:12.222009 140402235246464 interactiveshell.py:2882] Step 20350 | Loss: 0.0071 | Spent: 123.3 secs | LR: 0.000106
I0522 07:37:19.585205 140402235246464 interactiveshell.py:2882] Step 20400 | Loss: 0.0472 | Spent: 7.4 secs | LR: 0.000105
I0522 07:37:26.536268 140402235246464 interactiveshell.py:2882] Step 20450 | Loss: 0.0452 | Spent: 6.9 secs | LR: 0.000105
I0522 07:37:33.458113 140402235246464 interactiveshell.py:2882] Step 20500 | Loss: 0.0496 | Spent: 6.9 secs | LR: 0.000105
I0522 07:37:40.400771 140402235246464 interactiveshell.py:2882] Step 20550 | Loss: 0.0315 | Spent: 6.9 secs | LR: 0.000105
I0522 07:37:47.284709 140402235246464 interactiveshell.py:2882] Step 20600 | Loss: 0.0019 | Spent: 6.9 secs | LR: 0.000104
I0522 07:37:54.166136 140402235246464 interactiveshell.py:2882] Step 20650 | Loss: 0.0006 | Spent: 6.9 secs | LR: 0.000104
I0522 07:38:01.066666 140402235246464 interactiveshell.py:2882] Step 20700 | Loss: 0.0053 | Spent: 6.9 secs | LR: 0.000104
I0522 07:38:08.075107 140402235246464 interactiveshell.py:2882] Step 20750 | Loss: 0.1533 | Spent: 7.0 secs | LR: 0.000103
I0522 07:38:14.955051 140402235246464 interactiveshell.py:2882] Step 20800 | Loss: 0.0006 | Spent: 6.9 secs | LR: 0.000103
I0522 07:38:21.864099 140402235246464 interactiveshell.py:2882] Step 20850 | Loss: 0.0455 | Spent: 6.9 secs | LR: 0.000103
I0522 07:38:28.796928 140402235246464 interactiveshell.py:2882] Step 20900 | Loss: 0.0036 | Spent: 6.9 secs | LR: 0.000103
I0522 07:38:36.145951 140402235246464 interactiveshell.py:2882] Step 20950 | Loss: 0.0749 | Spent: 7.3 secs | LR: 0.000102
I0522 07:38:43.898322 140402235246464 interactiveshell.py:2882] Step 21000 | Loss: 0.0415 | Spent: 7.8 secs | LR: 0.000102
I0522 07:38:51.113587 140402235246464 interactiveshell.py:2882] Step 21050 | Loss: 0.0045 | Spent: 7.2 secs | LR: 0.000102
I0522 07:38:58.005207 140402235246464 interactiveshell.py:2882] Step 21100 | Loss: 0.0325 | Spent: 6.9 secs | LR: 0.000102
Reading ../data/test.txt
I0522 07:40:48.162676 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 07:40:48.163817 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:41:01.705455 140402235246464 interactiveshell.py:2882] Step 21150 | Loss: 0.0071 | Spent: 123.7 secs | LR: 0.000101
I0522 07:41:08.656645 140402235246464 interactiveshell.py:2882] Step 21200 | Loss: 0.0317 | Spent: 6.9 secs | LR: 0.000101
I0522 07:41:15.968762 140402235246464 interactiveshell.py:2882] Step 21250 | Loss: 0.0043 | Spent: 7.3 secs | LR: 0.000101
I0522 07:41:23.183834 140402235246464 interactiveshell.py:2882] Step 21300 | Loss: 0.0041 | Spent: 7.2 secs | LR: 0.000101
I0522 07:41:30.132901 140402235246464 interactiveshell.py:2882] Step 21350 | Loss: 0.0031 | Spent: 6.9 secs | LR: 0.000100
I0522 07:41:37.051254 140402235246464 interactiveshell.py:2882] Step 21400 | Loss: 0.0056 | Spent: 6.9 secs | LR: 0.000100
I0522 07:41:43.972737 140402235246464 interactiveshell.py:2882] Step 21450 | Loss: 0.0426 | Spent: 6.9 secs | LR: 0.000100
I0522 07:41:50.889841 140402235246464 interactiveshell.py:2882] Step 21500 | Loss: 0.0377 | Spent: 6.9 secs | LR: 0.000100
I0522 07:41:57.838263 140402235246464 interactiveshell.py:2882] Step 21550 | Loss: 0.0056 | Spent: 6.9 secs | LR: 0.000099
I0522 07:42:04.869266 140402235246464 interactiveshell.py:2882] Step 21600 | Loss: 0.0188 | Spent: 7.0 secs | LR: 0.000099
I0522 07:42:11.790609 140402235246464 interactiveshell.py:2882] Step 21650 | Loss: 0.0609 | Spent: 6.9 secs | LR: 0.000099
I0522 07:42:18.742780 140402235246464 interactiveshell.py:2882] Step 21700 | Loss: 0.0532 | Spent: 7.0 secs | LR: 0.000099
I0522 07:42:25.706228 140402235246464 interactiveshell.py:2882] Step 21750 | Loss: 0.0012 | Spent: 7.0 secs | LR: 0.000098
I0522 07:42:32.736461 140402235246464 interactiveshell.py:2882] Step 21800 | Loss: 0.0003 | Spent: 7.0 secs | LR: 0.000098
I0522 07:42:40.116590 140402235246464 interactiveshell.py:2882] Step 21850 | Loss: 0.0683 | Spent: 7.4 secs | LR: 0.000098
Reading ../data/test.txt
I0522 07:44:36.241599 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.896
I0522 07:44:36.242686 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:44:44.469997 140402235246464 interactiveshell.py:2882] Step 21900 | Loss: 0.0741 | Spent: 124.4 secs | LR: 0.000098
I0522 07:44:51.446656 140402235246464 interactiveshell.py:2882] Step 21950 | Loss: 0.0143 | Spent: 7.0 secs | LR: 0.000097
I0522 07:44:58.420819 140402235246464 interactiveshell.py:2882] Step 22000 | Loss: 0.0692 | Spent: 7.0 secs | LR: 0.000097
I0522 07:45:05.404268 140402235246464 interactiveshell.py:2882] Step 22050 | Loss: 0.1846 | Spent: 7.0 secs | LR: 0.000097
I0522 07:45:12.398221 140402235246464 interactiveshell.py:2882] Step 22100 | Loss: 0.0006 | Spent: 7.0 secs | LR: 0.000097
I0522 07:45:19.778395 140402235246464 interactiveshell.py:2882] Step 22150 | Loss: 0.0069 | Spent: 7.4 secs | LR: 0.000096
I0522 07:45:26.830363 140402235246464 interactiveshell.py:2882] Step 22200 | Loss: 0.0035 | Spent: 7.1 secs | LR: 0.000096
I0522 07:45:33.739139 140402235246464 interactiveshell.py:2882] Step 22250 | Loss: 0.0200 | Spent: 6.9 secs | LR: 0.000096
I0522 07:45:40.618125 140402235246464 interactiveshell.py:2882] Step 22300 | Loss: 0.0052 | Spent: 6.9 secs | LR: 0.000096
I0522 07:45:47.481179 140402235246464 interactiveshell.py:2882] Step 22350 | Loss: 0.0055 | Spent: 6.9 secs | LR: 0.000095
I0522 07:45:54.530311 140402235246464 interactiveshell.py:2882] Step 22400 | Loss: 0.0004 | Spent: 7.0 secs | LR: 0.000095
I0522 07:46:01.885726 140402235246464 interactiveshell.py:2882] Step 22450 | Loss: 0.0008 | Spent: 7.4 secs | LR: 0.000095
I0522 07:46:08.773677 140402235246464 interactiveshell.py:2882] Step 22500 | Loss: 0.0113 | Spent: 6.9 secs | LR: 0.000095
I0522 07:46:15.681271 140402235246464 interactiveshell.py:2882] Step 22550 | Loss: 0.0107 | Spent: 6.9 secs | LR: 0.000094
I0522 07:46:22.650953 140402235246464 interactiveshell.py:2882] Step 22600 | Loss: 0.0039 | Spent: 7.0 secs | LR: 0.000094
I0522 07:46:29.617185 140402235246464 interactiveshell.py:2882] Step 22650 | Loss: 0.0159 | Spent: 7.0 secs | LR: 0.000094
Reading ../data/test.txt
I0522 07:48:22.511684 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 07:48:22.512756 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:48:33.206284 140402235246464 interactiveshell.py:2882] Step 22700 | Loss: 0.0106 | Spent: 123.6 secs | LR: 0.000094
I0522 07:48:40.161927 140402235246464 interactiveshell.py:2882] Step 22750 | Loss: 0.0038 | Spent: 7.0 secs | LR: 0.000093
I0522 07:48:47.115803 140402235246464 interactiveshell.py:2882] Step 22800 | Loss: 0.0115 | Spent: 7.0 secs | LR: 0.000093
I0522 07:48:54.063798 140402235246464 interactiveshell.py:2882] Step 22850 | Loss: 0.0226 | Spent: 6.9 secs | LR: 0.000093
I0522 07:49:01.417218 140402235246464 interactiveshell.py:2882] Step 22900 | Loss: 0.0091 | Spent: 7.4 secs | LR: 0.000093
I0522 07:49:08.984493 140402235246464 interactiveshell.py:2882] Step 22950 | Loss: 0.0149 | Spent: 7.6 secs | LR: 0.000092
I0522 07:49:16.059848 140402235246464 interactiveshell.py:2882] Step 23000 | Loss: 0.0005 | Spent: 7.1 secs | LR: 0.000092
I0522 07:49:23.403229 140402235246464 interactiveshell.py:2882] Step 23050 | Loss: 0.0474 | Spent: 7.3 secs | LR: 0.000092
I0522 07:49:30.286821 140402235246464 interactiveshell.py:2882] Step 23100 | Loss: 0.0092 | Spent: 6.9 secs | LR: 0.000092
I0522 07:49:37.155311 140402235246464 interactiveshell.py:2882] Step 23150 | Loss: 0.0037 | Spent: 6.9 secs | LR: 0.000092
I0522 07:49:44.033272 140402235246464 interactiveshell.py:2882] Step 23200 | Loss: 0.0018 | Spent: 6.9 secs | LR: 0.000091
I0522 07:49:50.922340 140402235246464 interactiveshell.py:2882] Step 23250 | Loss: 0.0005 | Spent: 6.9 secs | LR: 0.000091
I0522 07:49:57.965357 140402235246464 interactiveshell.py:2882] Step 23300 | Loss: 0.0005 | Spent: 7.0 secs | LR: 0.000091
I0522 07:50:04.870715 140402235246464 interactiveshell.py:2882] Step 23350 | Loss: 0.0266 | Spent: 6.9 secs | LR: 0.000091
I0522 07:50:11.788060 140402235246464 interactiveshell.py:2882] Step 23400 | Loss: 0.0001 | Spent: 6.9 secs | LR: 0.000090
I0522 07:50:18.676223 140402235246464 interactiveshell.py:2882] Step 23450 | Loss: 0.0399 | Spent: 6.9 secs | LR: 0.000090
Reading ../data/test.txt
I0522 07:52:09.878131 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.907
I0522 07:52:09.879247 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:52:23.031547 140402235246464 interactiveshell.py:2882] Step 23500 | Loss: 0.0088 | Spent: 124.4 secs | LR: 0.000090
I0522 07:52:30.016274 140402235246464 interactiveshell.py:2882] Step 23550 | Loss: 0.0323 | Spent: 7.0 secs | LR: 0.000090
I0522 07:52:36.999931 140402235246464 interactiveshell.py:2882] Step 23600 | Loss: 0.0102 | Spent: 7.0 secs | LR: 0.000089
I0522 07:52:43.938783 140402235246464 interactiveshell.py:2882] Step 23650 | Loss: 0.0106 | Spent: 6.9 secs | LR: 0.000089
I0522 07:52:50.877477 140402235246464 interactiveshell.py:2882] Step 23700 | Loss: 0.0046 | Spent: 6.9 secs | LR: 0.000089
I0522 07:52:57.782223 140402235246464 interactiveshell.py:2882] Step 23750 | Loss: 0.0004 | Spent: 6.9 secs | LR: 0.000089
I0522 07:53:04.756621 140402235246464 interactiveshell.py:2882] Step 23800 | Loss: 0.0017 | Spent: 7.0 secs | LR: 0.000088
I0522 07:53:11.646239 140402235246464 interactiveshell.py:2882] Step 23850 | Loss: 0.0007 | Spent: 6.9 secs | LR: 0.000088
I0522 07:53:18.823969 140402235246464 interactiveshell.py:2882] Step 23900 | Loss: 0.0006 | Spent: 7.2 secs | LR: 0.000088
I0522 07:53:26.076741 140402235246464 interactiveshell.py:2882] Step 23950 | Loss: 0.0018 | Spent: 7.3 secs | LR: 0.000088
I0522 07:53:32.956920 140402235246464 interactiveshell.py:2882] Step 24000 | Loss: 0.0072 | Spent: 6.9 secs | LR: 0.000088
I0522 07:53:39.919185 140402235246464 interactiveshell.py:2882] Step 24050 | Loss: 0.0062 | Spent: 7.0 secs | LR: 0.000087
I0522 07:53:46.795558 140402235246464 interactiveshell.py:2882] Step 24100 | Loss: 0.0001 | Spent: 6.9 secs | LR: 0.000087
I0522 07:53:53.822724 140402235246464 interactiveshell.py:2882] Step 24150 | Loss: 0.0039 | Spent: 7.0 secs | LR: 0.000087
I0522 07:54:00.746738 140402235246464 interactiveshell.py:2882] Step 24200 | Loss: 0.0715 | Spent: 6.9 secs | LR: 0.000087
Reading ../data/test.txt
I0522 07:55:56.169624 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 07:55:56.170870 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:56:06.173203 140402235246464 interactiveshell.py:2882] Step 24250 | Loss: 0.0041 | Spent: 125.4 secs | LR: 0.000086
I0522 07:56:13.566184 140402235246464 interactiveshell.py:2882] Step 24300 | Loss: 0.0081 | Spent: 7.4 secs | LR: 0.000086
I0522 07:56:20.516254 140402235246464 interactiveshell.py:2882] Step 24350 | Loss: 0.0123 | Spent: 6.9 secs | LR: 0.000086
I0522 07:56:27.463808 140402235246464 interactiveshell.py:2882] Step 24400 | Loss: 0.0010 | Spent: 6.9 secs | LR: 0.000086
I0522 07:56:34.394325 140402235246464 interactiveshell.py:2882] Step 24450 | Loss: 0.0080 | Spent: 6.9 secs | LR: 0.000086
I0522 07:56:41.379140 140402235246464 interactiveshell.py:2882] Step 24500 | Loss: 0.0022 | Spent: 7.0 secs | LR: 0.000085
I0522 07:56:48.288330 140402235246464 interactiveshell.py:2882] Step 24550 | Loss: 0.0339 | Spent: 6.9 secs | LR: 0.000085
I0522 07:56:55.152711 140402235246464 interactiveshell.py:2882] Step 24600 | Loss: 0.1065 | Spent: 6.9 secs | LR: 0.000085
I0522 07:57:02.027166 140402235246464 interactiveshell.py:2882] Step 24650 | Loss: 0.0094 | Spent: 6.9 secs | LR: 0.000085
I0522 07:57:08.908240 140402235246464 interactiveshell.py:2882] Step 24700 | Loss: 0.0182 | Spent: 6.9 secs | LR: 0.000085
I0522 07:57:15.801383 140402235246464 interactiveshell.py:2882] Step 24750 | Loss: 0.0037 | Spent: 6.9 secs | LR: 0.000084
I0522 07:57:23.148447 140402235246464 interactiveshell.py:2882] Step 24800 | Loss: 0.0008 | Spent: 7.3 secs | LR: 0.000084
I0522 07:57:30.208454 140402235246464 interactiveshell.py:2882] Step 24850 | Loss: 0.0054 | Spent: 7.1 secs | LR: 0.000084
I0522 07:57:37.107380 140402235246464 interactiveshell.py:2882] Step 24900 | Loss: 0.0012 | Spent: 6.9 secs | LR: 0.000084
I0522 07:57:44.024369 140402235246464 interactiveshell.py:2882] Step 24950 | Loss: 0.0016 | Spent: 6.9 secs | LR: 0.000083
I0522 07:57:51.058248 140402235246464 interactiveshell.py:2882] Step 25000 | Loss: 0.0019 | Spent: 7.0 secs | LR: 0.000083
Reading ../data/test.txt
I0522 07:59:43.601391 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 07:59:43.602468 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 07:59:54.857756 140402235246464 interactiveshell.py:2882] Step 25050 | Loss: 0.0125 | Spent: 123.8 secs | LR: 0.000083
I0522 08:00:02.181202 140402235246464 interactiveshell.py:2882] Step 25100 | Loss: 0.0003 | Spent: 7.3 secs | LR: 0.000083
I0522 08:00:09.408655 140402235246464 interactiveshell.py:2882] Step 25150 | Loss: 0.0099 | Spent: 7.2 secs | LR: 0.000083
I0522 08:00:16.348746 140402235246464 interactiveshell.py:2882] Step 25200 | Loss: 0.0005 | Spent: 6.9 secs | LR: 0.000082
I0522 08:00:23.239723 140402235246464 interactiveshell.py:2882] Step 25250 | Loss: 0.0846 | Spent: 6.9 secs | LR: 0.000082
I0522 08:00:30.186932 140402235246464 interactiveshell.py:2882] Step 25300 | Loss: 0.0080 | Spent: 6.9 secs | LR: 0.000082
I0522 08:00:37.237772 140402235246464 interactiveshell.py:2882] Step 25350 | Loss: 0.0011 | Spent: 7.0 secs | LR: 0.000082
I0522 08:00:44.136770 140402235246464 interactiveshell.py:2882] Step 25400 | Loss: 0.0272 | Spent: 6.9 secs | LR: 0.000082
I0522 08:00:51.059099 140402235246464 interactiveshell.py:2882] Step 25450 | Loss: 0.0149 | Spent: 6.9 secs | LR: 0.000081
I0522 08:00:57.947772 140402235246464 interactiveshell.py:2882] Step 25500 | Loss: 0.0003 | Spent: 6.9 secs | LR: 0.000081
I0522 08:01:04.843799 140402235246464 interactiveshell.py:2882] Step 25550 | Loss: 0.0103 | Spent: 6.9 secs | LR: 0.000081
I0522 08:01:11.742506 140402235246464 interactiveshell.py:2882] Step 25600 | Loss: 0.0596 | Spent: 6.9 secs | LR: 0.000081
I0522 08:01:19.223851 140402235246464 interactiveshell.py:2882] Step 25650 | Loss: 0.0047 | Spent: 7.5 secs | LR: 0.000080
I0522 08:01:26.606640 140402235246464 interactiveshell.py:2882] Step 25700 | Loss: 0.0052 | Spent: 7.4 secs | LR: 0.000080
I0522 08:01:33.528133 140402235246464 interactiveshell.py:2882] Step 25750 | Loss: 0.0001 | Spent: 6.9 secs | LR: 0.000080
I0522 08:01:40.433216 140402235246464 interactiveshell.py:2882] Step 25800 | Loss: 0.0486 | Spent: 6.9 secs | LR: 0.000080
Reading ../data/test.txt
I0522 08:03:29.172500 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.911
I0522 08:03:29.173569 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 08:03:42.907573 140402235246464 interactiveshell.py:2882] Step 25850 | Loss: 0.0045 | Spent: 122.5 secs | LR: 0.000080
I0522 08:03:49.887495 140402235246464 interactiveshell.py:2882] Step 25900 | Loss: 0.0451 | Spent: 7.0 secs | LR: 0.000079
I0522 08:03:56.875394 140402235246464 interactiveshell.py:2882] Step 25950 | Loss: 0.0077 | Spent: 7.0 secs | LR: 0.000079
I0522 08:04:04.268599 140402235246464 interactiveshell.py:2882] Step 26000 | Loss: 0.0820 | Spent: 7.4 secs | LR: 0.000079
I0522 08:04:11.414683 140402235246464 interactiveshell.py:2882] Step 26050 | Loss: 0.0040 | Spent: 7.1 secs | LR: 0.000079
I0522 08:04:18.299170 140402235246464 interactiveshell.py:2882] Step 26100 | Loss: 0.0016 | Spent: 6.9 secs | LR: 0.000079
I0522 08:04:25.225837 140402235246464 interactiveshell.py:2882] Step 26150 | Loss: 0.0110 | Spent: 6.9 secs | LR: 0.000078
I0522 08:04:32.513306 140402235246464 interactiveshell.py:2882] Step 26200 | Loss: 0.0137 | Spent: 7.3 secs | LR: 0.000078
I0522 08:04:40.098313 140402235246464 interactiveshell.py:2882] Step 26250 | Loss: 0.0035 | Spent: 7.6 secs | LR: 0.000078
I0522 08:04:47.003458 140402235246464 interactiveshell.py:2882] Step 26300 | Loss: 0.0008 | Spent: 6.9 secs | LR: 0.000078
I0522 08:04:53.916704 140402235246464 interactiveshell.py:2882] Step 26350 | Loss: 0.0004 | Spent: 6.9 secs | LR: 0.000078
I0522 08:05:00.854146 140402235246464 interactiveshell.py:2882] Step 26400 | Loss: 0.0009 | Spent: 6.9 secs | LR: 0.000077
I0522 08:05:07.782310 140402235246464 interactiveshell.py:2882] Step 26450 | Loss: 0.1201 | Spent: 6.9 secs | LR: 0.000077
I0522 08:05:14.723573 140402235246464 interactiveshell.py:2882] Step 26500 | Loss: 0.0172 | Spent: 6.9 secs | LR: 0.000077
I0522 08:05:21.903690 140402235246464 interactiveshell.py:2882] Step 26550 | Loss: 0.0602 | Spent: 7.2 secs | LR: 0.000077
Reading ../data/test.txt
I0522 08:07:16.824832 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.903
I0522 08:07:16.825890 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 08:07:26.135273 140402235246464 interactiveshell.py:2882] Step 26600 | Loss: 0.0039 | Spent: 124.2 secs | LR: 0.000077
I0522 08:07:33.126867 140402235246464 interactiveshell.py:2882] Step 26650 | Loss: 0.0117 | Spent: 7.0 secs | LR: 0.000076
I0522 08:07:40.094811 140402235246464 interactiveshell.py:2882] Step 26700 | Loss: 0.0010 | Spent: 7.0 secs | LR: 0.000076
I0522 08:07:47.176261 140402235246464 interactiveshell.py:2882] Step 26750 | Loss: 0.0040 | Spent: 7.1 secs | LR: 0.000076
I0522 08:07:54.152355 140402235246464 interactiveshell.py:2882] Step 26800 | Loss: 0.0013 | Spent: 7.0 secs | LR: 0.000076
I0522 08:08:01.274702 140402235246464 interactiveshell.py:2882] Step 26850 | Loss: 0.0722 | Spent: 7.1 secs | LR: 0.000076
I0522 08:08:08.677888 140402235246464 interactiveshell.py:2882] Step 26900 | Loss: 0.0124 | Spent: 7.4 secs | LR: 0.000075
I0522 08:08:15.626162 140402235246464 interactiveshell.py:2882] Step 26950 | Loss: 0.0004 | Spent: 6.9 secs | LR: 0.000075
I0522 08:08:22.557715 140402235246464 interactiveshell.py:2882] Step 27000 | Loss: 0.0594 | Spent: 6.9 secs | LR: 0.000075
I0522 08:08:29.453126 140402235246464 interactiveshell.py:2882] Step 27050 | Loss: 0.0013 | Spent: 6.9 secs | LR: 0.000075
I0522 08:08:36.413550 140402235246464 interactiveshell.py:2882] Step 27100 | Loss: 0.0012 | Spent: 7.0 secs | LR: 0.000075
I0522 08:08:43.321474 140402235246464 interactiveshell.py:2882] Step 27150 | Loss: 0.0589 | Spent: 6.9 secs | LR: 0.000075
I0522 08:08:50.343748 140402235246464 interactiveshell.py:2882] Step 27200 | Loss: 0.0058 | Spent: 7.0 secs | LR: 0.000074
I0522 08:08:57.311847 140402235246464 interactiveshell.py:2882] Step 27250 | Loss: 0.0080 | Spent: 7.0 secs | LR: 0.000074
I0522 08:09:04.288476 140402235246464 interactiveshell.py:2882] Step 27300 | Loss: 0.0045 | Spent: 7.0 secs | LR: 0.000074
I0522 08:09:11.222276 140402235246464 interactiveshell.py:2882] Step 27350 | Loss: 0.0002 | Spent: 6.9 secs | LR: 0.000074
Reading ../data/test.txt
I0522 08:11:04.479198 140402235246464 interactiveshell.py:2882] Evaluation: Testing Accuracy: 0.910
I0522 08:11:04.480303 140402235246464 interactiveshell.py:2882] Best Accuracy: 0.914
Reading ../data/train.txt
I0522 08:11:16.248610 140402235246464 interactiveshell.py:2882] Step 27400 | Loss: 0.0044 | Spent: 125.0 secs | LR: 0.000074
I0522 08:11:23.320042 140402235246464 interactiveshell.py:2882] Step 27450 | Loss: 0.0911 | Spent: 7.1 secs | LR: 0.000073
I0522 08:11:30.620723 140402235246464 interactiveshell.py:2882] Step 27500 | Loss: 0.0029 | Spent: 7.3 secs | LR: 0.000073
I0522 08:11:37.627379 140402235246464 interactiveshell.py:2882] Step 27550 | Loss: 0.0037 | Spent: 7.0 secs | LR: 0.000073
---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-8-67a2a49c8e35> in <module>()
     28   for texts, labels in dataset(is_training=True, params=params):
     29     with tf.GradientTape() as tape:
---> 30       logits = model(texts, training=True)
     31       loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=labels, logits=logits)
     32       loss = tf.reduce_mean(loss)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
    658           with base_layer_utils.autocast_context_manager(
    659               input_list, self._mixed_precision_policy.should_cast_variables):
--> 660             outputs = self.call(inputs, *args, **kwargs)
    661           self._handle_activity_regularization(inputs, outputs)
    662           self._set_mask_metadata(inputs, outputs, previous_mask)

<ipython-input-5-d6d485918964> in call(self, inputs, training)
     37 
     38     x = tf.reshape(x, (batch_sz*10, 10, rnn_units))
---> 39     x = self.drop2(x, training=training)
     40     x = self.rnn2(x)
     41     x = tf.reduce_max(x, 1)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
    658           with base_layer_utils.autocast_context_manager(
    659               input_list, self._mixed_precision_policy.should_cast_variables):
--> 660             outputs = self.call(inputs, *args, **kwargs)
    661           self._handle_activity_regularization(inputs, outputs)
    662           self._set_mask_metadata(inputs, outputs, previous_mask)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/layers/core.py in call(self, inputs, training)
    157     output = tf_utils.smart_cond(training,
    158                                  dropped_inputs,
--> 159                                  lambda: array_ops.identity(inputs))
    160     return output
    161 

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/utils/tf_utils.py in smart_cond(pred, true_fn, false_fn, name)
     54         pred, true_fn=true_fn, false_fn=false_fn, name=name)
     55   return smart_module.smart_cond(
---> 56       pred, true_fn=true_fn, false_fn=false_fn, name=name)
     57 
     58 

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/smart_cond.py in smart_cond(pred, true_fn, false_fn, name)
     52   if pred_value is not None:
     53     if pred_value:
---> 54       return true_fn()
     55     else:
     56       return false_fn()

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/layers/core.py in dropped_inputs()
    153           noise_shape=self._get_noise_shape(inputs),
    154           seed=self.seed,
--> 155           rate=self.rate)
    156 
    157     output = tf_utils.smart_cond(training,

/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
    505                 'in a future version' if date is None else ('after %s' % date),
    506                 instructions)
--> 507       return func(*args, **kwargs)
    508 
    509     doc = _add_deprecated_arg_notice_to_docstring(

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/nn_ops.py in dropout(x, keep_prob, noise_shape, seed, name, rate)
   4074     raise ValueError("You must provide a rate to dropout.")
   4075 
-> 4076   return dropout_v2(x, rate, noise_shape=noise_shape, seed=seed, name=name)
   4077 
   4078 

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/nn_ops.py in dropout_v2(x, rate, noise_shape, seed, name)
   4144     # and subtract 1.0.
   4145     random_tensor = random_ops.random_uniform(
-> 4146         noise_shape, seed=seed, dtype=x.dtype)
   4147     keep_prob = 1 - rate
   4148     scale = 1 / keep_prob

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/random_ops.py in random_uniform(shape, minval, maxval, dtype, seed, name)
    246     else:
    247       rnd = gen_random_ops.random_uniform(shape, dtype, seed=seed1, seed2=seed2)
--> 248       return math_ops.add(rnd * (maxval - minval), minval, name=name)
    249 
    250 

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py in binary_op_wrapper(x, y)
    861     with ops.name_scope(None, op_name, [x, y]) as name:
    862       if isinstance(x, ops.Tensor) and isinstance(y, ops.Tensor):
--> 863         return func(x, y, name=name)
    864       elif not isinstance(y, sparse_tensor.SparseTensor):
    865         try:

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_math_ops.py in sub(x, y, name)
  10607       _result = _pywrap_tensorflow.TFE_Py_FastPathExecute(
  10608         _ctx._context_handle, _ctx._thread_local_data.device_name, "Sub",
> 10609         name, _ctx._post_execution_callbacks, x, y)
  10610       return _result
  10611     except _core._FallbackException:

KeyboardInterrupt: