In [34]:
#imports
import os
import pandas as pd
import numpy as np
import tensorflow as tf
import tensorflow.contrib.learn as skflow
from scipy.stats import zscore
from sklearn.cross_validation import KFold
from sklearn import metrics
from sklearn import preprocessing
from sklearn.cross_validation import train_test_split
In [35]:
#define common functions
# Encode text values to dummy variables(i.e. [1,0,0],[0,1,0],[0,0,1] for red,green,blue)
def encode_text_dummy(df,name):
dummies = pd.get_dummies(df[name])
for x in dummies.columns:
dummy_name = "{}-{}".format(name,x)
df[dummy_name] = dummies[x]
df.drop(name, axis=1, inplace=True)
# Encode text values to indexes(i.e. [1],[2],[3] for red,green,blue).
def encode_text_index(df,name):
le = preprocessing.LabelEncoder()
df[name] = le.fit_transform(df[name])
return le.classes_
# Encode a numeric column as zscores
def encode_numeric_zscore(df,name,mean=None,sd=None):
if mean is None:
mean = df[name].mean()
if sd is None:
sd = df[name].std()
df[name] = (df[name]-mean)/sd
# Convert all missing values in the specified column to the median
def missing_median(df, name):
med = df[name].median()
df[name] = df[name].fillna(med)
# Convert a Pandas dataframe to the x,y inputs that TensorFlow needs
def to_xy(df,target):
result = []
for x in df.columns:
if x != target:
result.append(x)
# find out the type of the target column. Is it really this hard? :(
target_type = df[target].dtypes
target_type = target_type[0] if hasattr(target_type, '__iter__') else target_type
print(target_type)
# Encode to int for classification, float otherwise. TensorFlow likes 32 bits.
if target_type in (np.int64, np.int32):
# Classification
return df.as_matrix(result).astype(np.float32),df.as_matrix([target]).astype(np.int32)
else:
# Regression
return df.as_matrix(result).astype(np.float32),df.as_matrix([target]).astype(np.float32)
# setup exponential decay function
def exp_decay(global_step):
return tf.train.exponential_decay(
learning_rate=0.01, global_step=global_step,
decay_steps=100, decay_rate=0.001)
In [36]:
#Read Input CSV file
path = "./data/"
inputFilePath = os.path.join(path, "oronite.csv")
#df = pd.read_csv(inputFilePath, compression="gzip", header=0, na_values=['NULL'])
df = pd.read_csv(inputFilePath, header=0, na_values=['NULL'])
In [37]:
#show headers
#headers = list(df.columns.values)
#print(headers)
print(df.columns.values)
['\ufeffOR-F Code' 'D' 'PD' 'B' 'MD' 'F' 'FM' 'ZN' 'DE' 'IN' 'O' 'VI' 'DI'
'LAB_CODE' 'Result_Code' 'TEST_RESULT_VALUE']
In [38]:
#Sort dataset
#df.sort_values(by="SortKey",ascending=True)
#shuffle dataset. Unnecessary in this case because already sorted by guid
np.random.seed(42)
df = df.reindex(np.random.permutation(df.index))
df.reset_index(inplace=True, drop=True)
In [39]:
df.drop('\ufeffOR-F Code', axis=1, inplace=True)
In [40]:
#encode result_code and lab_code as numbers
encode_text_dummy(df, 'LAB_CODE')
encode_text_dummy(df, 'Result_Code')
In [41]:
df
Out[41]:
D
PD
B
MD
F
FM
ZN
DE
IN
O
VI
DI
TEST_RESULT_VALUE
LAB_CODE-AL
LAB_CODE-EG
LAB_CODE-LT
LAB_CODE-SR
Result_Code-DP1--WDN
0
0.000
0.30
80.13
0.0
0.025
0.0
1.377
2.721
1.150
0.00
4.00
9.580
223.2
0.0
0.0
0.0
1.0
1.0
1
0.000
0.10
87.02
0.0
0.023
0.0
1.457
4.087
0.000
0.00
0.00
6.670
445.7
0.0
0.0
1.0
0.0
1.0
2
2.510
0.20
77.31
0.0
0.020
0.0
1.109
3.442
0.214
0.00
12.50
4.068
314.1
0.0
0.0
0.0
1.0
1.0
3
0.000
0.30
82.10
0.0
0.010
0.0
1.227
4.303
0.170
0.00
4.90
5.676
214.3
0.0
0.0
1.0
0.0
1.0
4
0.000
0.20
84.75
0.0
0.025
0.0
1.251
3.072
0.202
0.00
6.20
4.304
215.3
0.0
0.0
1.0
0.0
1.0
5
0.000
0.00
77.13
0.0
0.025
0.0
1.377
3.569
0.700
0.00
12.20
5.000
207.0
0.0
1.0
0.0
0.0
1.0
6
0.000
0.00
74.80
0.0
0.020
0.0
2.094
5.849
0.150
0.00
9.00
6.329
252.6
0.0
0.0
0.0
1.0
1.0
7
0.000
0.20
83.20
0.0
0.025
0.0
1.249
3.088
0.199
0.00
7.12
4.925
210.5
0.0
0.0
1.0
0.0
1.0
8
0.000
0.00
74.80
0.0
0.020
0.0
2.094
5.849
0.150
0.00
9.00
6.329
321.1
0.0
0.0
0.0
1.0
1.0
9
0.000
0.20
84.04
0.0
0.025
0.0
0.697
1.980
0.100
0.00
10.00
2.673
477.6
0.0
1.0
0.0
0.0
1.0
10
0.000
0.30
75.45
0.0
0.020
0.0
1.377
4.512
0.450
0.03
7.00
10.000
250.0
0.0
0.0
1.0
0.0
1.0
11
0.000
0.15
79.84
0.0
0.050
0.0
1.358
5.096
0.200
0.00
6.50
6.800
263.1
0.0
0.0
1.0
0.0
1.0
12
0.000
0.20
78.77
0.0
0.025
0.0
1.269
3.337
0.200
0.00
8.40
7.800
200.0
0.0
0.0
1.0
0.0
1.0
13
0.000
0.00
80.18
0.0
0.025
0.0
1.485
4.230
0.304
0.00
5.90
7.879
300.2
0.0
0.0
1.0
0.0
1.0
14
0.000
0.00
76.92
0.0
0.025
0.0
1.377
4.295
0.200
0.00
9.50
7.000
213.3
0.0
0.0
1.0
0.0
1.0
15
0.000
0.00
78.64
0.0
0.025
0.0
1.377
3.680
0.200
0.00
7.50
8.000
237.6
0.0
0.0
1.0
0.0
1.0
16
0.000
0.20
84.04
0.0
0.025
0.0
0.697
1.980
0.100
0.00
10.00
2.673
432.0
0.0
1.0
0.0
0.0
1.0
17
0.000
0.00
78.53
0.0
0.010
0.0
1.044
4.150
0.202
0.00
8.30
6.233
181.3
0.0
0.0
1.0
0.0
1.0
18
0.809
0.00
75.10
0.0
0.020
0.0
2.061
5.471
0.154
0.00
9.20
6.233
207.1
0.0
0.0
1.0
0.0
1.0
19
0.590
0.30
79.61
0.0
0.050
0.0
1.386
3.079
0.862
0.00
6.80
7.325
278.7
0.0
0.0
1.0
0.0
1.0
20
0.780
0.00
78.99
0.0
0.025
0.0
1.485
4.722
0.813
0.00
5.50
7.684
259.0
0.0
0.0
1.0
0.0
1.0
21
0.000
0.30
75.45
0.0
0.020
0.0
1.377
4.512
0.450
0.03
7.00
10.000
220.9
0.0
0.0
1.0
0.0
1.0
22
0.000
0.15
72.79
0.0
0.025
0.0
1.377
3.851
0.950
0.00
11.10
8.865
284.7
0.0
0.0
1.0
0.0
1.0
23
1.200
0.00
77.53
0.0
0.025
0.0
1.377
3.569
0.700
0.00
7.60
8.000
187.8
0.0
0.0
1.0
0.0
1.0
24
0.000
0.00
78.64
0.0
0.025
0.0
1.377
3.680
0.200
0.00
7.50
8.000
228.0
0.0
0.0
1.0
0.0
1.0
25
0.000
0.30
80.04
0.0
0.025
0.0
1.377
2.751
0.800
0.00
5.50
8.500
158.3
0.0
0.0
0.0
1.0
1.0
26
0.000
0.20
74.40
0.0
0.020
0.0
2.104
5.878
0.150
0.00
9.20
6.408
187.2
0.0
0.0
1.0
0.0
1.0
27
0.000
0.00
77.86
0.0
0.050
0.0
1.377
3.851
0.950
0.00
6.90
8.300
201.5
0.0
0.0
1.0
0.0
1.0
28
0.000
0.00
55.80
0.0
0.020
0.0
2.104
5.979
0.153
0.00
28.00
7.000
236.3
0.0
1.0
0.0
0.0
1.0
29
0.000
0.20
79.25
0.0
0.000
0.0
0.000
0.000
0.000
0.00
8.95
0.000
197.7
0.0
0.0
1.0
0.0
1.0
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
132
0.000
0.10
78.16
0.0
0.025
0.0
1.398
3.446
0.699
0.00
8.30
7.879
235.6
0.0
0.0
1.0
0.0
1.0
133
0.000
0.00
78.67
0.0
0.025
0.0
1.549
4.512
1.000
0.00
6.50
7.000
219.7
0.0
0.0
1.0
0.0
1.0
134
0.662
0.20
79.55
0.0
0.010
0.0
1.356
4.595
0.201
0.00
8.90
4.535
321.1
0.0
0.0
0.0
1.0
1.0
135
0.000
0.20
83.20
0.0
0.025
0.0
1.249
3.088
0.199
0.00
7.12
4.925
221.9
0.0
0.0
1.0
0.0
1.0
136
0.000
0.30
78.92
0.0
0.025
0.0
1.377
2.721
1.150
0.00
5.20
9.580
183.9
0.0
0.0
0.0
1.0
1.0
137
0.000
0.00
78.75
0.0
0.057
0.0
1.585
4.205
1.138
0.00
4.70
9.555
227.8
0.0
0.0
1.0
0.0
1.0
138
0.000
0.20
83.18
0.0
0.025
0.0
1.249
3.102
0.199
0.00
7.12
4.925
234.7
0.0
0.0
1.0
0.0
1.0
139
0.790
0.00
79.33
0.0
0.020
0.0
1.400
4.770
1.000
0.00
5.30
7.880
275.8
0.0
0.0
1.0
0.0
1.0
140
0.000
0.30
75.45
0.0
0.020
0.0
1.377
4.512
0.450
0.03
7.00
10.000
206.0
0.0
0.0
1.0
0.0
1.0
141
0.000
0.00
79.06
0.0
0.057
0.0
1.585
4.205
1.138
0.00
4.40
9.555
202.9
0.0
0.0
1.0
0.0
1.0
142
0.000
0.30
79.82
0.0
0.025
0.0
1.377
2.721
1.150
0.00
4.30
9.580
231.5
0.0
0.0
0.0
1.0
1.0
143
0.510
0.00
81.20
0.0
0.020
0.0
1.109
3.442
0.214
0.00
8.80
4.068
340.0
0.0
0.0
0.0
1.0
1.0
144
0.830
0.30
79.07
0.0
0.050
0.0
1.485
3.034
0.861
0.00
6.00
8.373
324.0
0.0
0.0
0.0
1.0
1.0
145
0.000
0.30
76.13
0.0
0.025
0.0
1.545
3.114
0.150
0.00
12.90
5.300
432.7
0.0
1.0
0.0
0.0
1.0
146
0.648
0.00
81.78
0.0
0.025
0.0
1.573
3.446
0.699
0.00
5.00
6.832
276.8
0.0
0.0
1.0
0.0
1.0
147
0.000
0.20
83.72
0.0
0.025
0.0
1.251
3.126
0.202
0.00
6.50
4.974
182.6
0.0
0.0
1.0
0.0
1.0
148
0.510
0.00
81.20
0.0
0.020
0.0
1.109
3.442
0.214
0.00
8.80
4.068
239.2
0.0
0.0
0.0
1.0
1.0
149
0.944
0.00
75.00
0.0
0.020
0.0
2.094
5.849
0.150
0.00
8.80
6.329
240.1
0.0
0.0
1.0
0.0
1.0
150
0.000
0.00
74.80
0.0
0.020
0.0
2.082
5.829
0.142
0.00
9.00
6.233
199.9
0.0
0.0
1.0
0.0
1.0
151
0.704
0.00
81.32
0.0
0.025
0.0
1.463
4.089
0.200
0.00
4.70
7.500
198.0
0.0
0.0
1.0
0.0
1.0
152
0.000
0.00
78.90
0.0
0.025
0.0
1.377
4.915
0.500
0.00
5.50
8.000
264.7
0.0
0.0
1.0
0.0
1.0
153
0.000
0.10
75.51
0.0
0.025
0.0
1.377
3.851
0.950
0.00
8.40
9.050
244.7
0.0
0.0
1.0
0.0
1.0
154
0.000
0.20
78.15
0.0
0.025
0.0
1.549
4.346
0.000
0.00
10.20
4.960
341.7
0.0
0.0
1.0
0.0
1.0
155
0.000
0.50
69.63
0.0
0.025
0.0
1.377
2.721
2.750
0.00
12.90
9.250
215.3
0.0
0.0
0.0
1.0
1.0
156
0.000
0.30
76.52
0.0
0.020
0.0
1.379
4.312
0.402
0.00
7.10
9.967
214.5
0.0
0.0
1.0
0.0
1.0
157
0.000
0.15
81.22
0.0
0.050
0.0
1.358
5.096
0.200
0.00
7.10
4.830
242.3
0.0
0.0
1.0
0.0
1.0
158
0.000
0.20
78.90
0.0
0.010
0.0
1.377
4.852
0.200
0.00
9.30
4.500
245.5
0.0
0.0
1.0
0.0
1.0
159
0.000
0.30
81.10
0.0
0.010
0.0
1.250
4.289
0.181
0.00
5.90
5.771
222.6
0.0
0.0
1.0
0.0
1.0
160
0.000
0.20
74.69
0.0
0.025
0.0
1.377
3.696
0.450
0.00
9.80
9.000
193.9
0.0
0.0
1.0
0.0
1.0
161
0.944
0.00
75.00
0.0
0.020
0.0
2.082
5.829
0.142
0.00
8.80
6.233
230.7
0.0
0.0
1.0
0.0
1.0
162 rows × 18 columns
In [42]:
print(df.columns.values)
['D' 'PD' 'B' 'MD' 'F' 'FM' 'ZN' 'DE' 'IN' 'O' 'VI' 'DI'
'TEST_RESULT_VALUE' 'LAB_CODE-AL' 'LAB_CODE-EG' 'LAB_CODE-LT'
'LAB_CODE-SR' 'Result_Code-DP1--WDN']
In [44]:
#encode all numeric values to zscored values
#encode_numeric_zscore(df, 'AW')
encode_numeric_zscore(df, 'D')
encode_numeric_zscore(df, 'PD')
encode_numeric_zscore(df, 'B')
encode_numeric_zscore(df, 'MD')
encode_numeric_zscore(df, 'F')
encode_numeric_zscore(df, 'FM')
encode_numeric_zscore(df, 'ZN')
encode_numeric_zscore(df, 'DE')
encode_numeric_zscore(df, 'IN')
encode_numeric_zscore(df, 'O')
encode_numeric_zscore(df, 'VI')
encode_numeric_zscore(df, 'DI')
In [45]:
#discard rows where z-score > 2
df.fillna(0)
df
Out[45]:
D
PD
B
MD
F
FM
ZN
DE
IN
O
VI
DI
TEST_RESULT_VALUE
LAB_CODE-AL
LAB_CODE-EG
LAB_CODE-LT
LAB_CODE-SR
Result_Code-DP1--WDN
0
-0.516318
1.246489
0.166940
-0.078567
-0.239846
-0.110968
-0.030189
-1.151937
1.474092
-0.177906
-0.987497
1.455932
223.2
0.0
0.0
0.0
1.0
1.0
1
-0.516318
-0.287943
1.604487
-0.078567
-0.414869
-0.110968
0.253734
0.305958
-1.152751
-0.177906
-2.077384
0.053231
445.7
0.0
0.0
1.0
0.0
1.0
2
6.530478
0.479273
-0.421432
-0.078567
-0.677403
-0.110968
-0.981330
-0.382433
-0.663930
-0.177906
1.328513
-1.201005
314.1
0.0
0.0
0.0
1.0
1.0
3
-0.516318
1.246489
0.577965
-0.078567
-1.552516
-0.110968
-0.562544
0.536489
-0.764435
-0.177906
-0.742272
-0.425904
214.3
0.0
0.0
1.0
0.0
1.0
4
-0.516318
0.479273
1.130868
-0.078567
-0.239846
-0.110968
-0.477367
-0.777324
-0.691340
-0.177906
-0.388059
-1.087246
215.3
0.0
0.0
1.0
0.0
1.0
5
-0.516318
-1.055158
-0.458988
-0.078567
-0.239846
-0.110968
-0.030189
-0.246889
0.446197
-0.177906
1.246772
-0.751755
207.0
0.0
1.0
0.0
0.0
1.0
6
-0.516318
-1.055158
-0.945125
-0.078567
-0.677403
-0.110968
2.514468
2.186493
-0.810119
-0.177906
0.374862
-0.111140
252.6
0.0
0.0
0.0
1.0
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In [46]:
# Create x(predictors) and y (expected outcome)
x,y = to_xy(df, "TEST_RESULT_VALUE")
float64
In [47]:
#Split into test/train
x_train, x_test, y_train, y_test = train_test_split(x,y,test_size=0.25, random_state=45)
In [52]:
# Create a deep neural network with 3 hidden layers of 105,50,25,12,5
regressor = skflow.TensorFlowDNNRegressor(hidden_units=[85, 40, 20, 10], learning_rate=0.01, steps=300000)
#early_stop = skflow.monitors.ValidationMonitor(x_test,y_test,early_stopping_rounds=2000, print_steps=50)
In [ ]:
#Fit/train neural network
regressor.fit(x_train,y_train)
Step #100, epoch #25, avg. train loss: 26694.48438
Step #200, epoch #50, avg. train loss: 4071.89160
Step #300, epoch #75, avg. train loss: 1306.95129
Step #400, epoch #100, avg. train loss: 1132.84021
Step #500, epoch #125, avg. train loss: 1031.47119
Step #600, epoch #150, avg. train loss: 953.54272
Step #700, epoch #175, avg. train loss: 891.61108
Step #800, epoch #200, avg. train loss: 835.11084
Step #900, epoch #225, avg. train loss: 773.07153
Step #1000, epoch #250, avg. train loss: 722.12128
Step #1100, epoch #275, avg. train loss: 681.34680
Step #1200, epoch #300, avg. train loss: 646.50403
Step #1300, epoch #325, avg. train loss: 606.13226
Step #1400, epoch #350, avg. train loss: 576.56317
Step #1500, epoch #375, avg. train loss: 548.33429
Step #1600, epoch #400, avg. train loss: 525.23633
Step #1700, epoch #425, avg. train loss: 506.14227
Step #1800, epoch #450, avg. train loss: 487.63281
Step #1900, epoch #475, avg. train loss: 470.48450
Step #2000, epoch #500, avg. train loss: 454.15811
Step #2100, epoch #525, avg. train loss: 440.59433
Step #2200, epoch #550, avg. train loss: 429.48279
Step #2300, epoch #575, avg. train loss: 421.10309
Step #2400, epoch #600, avg. train loss: 410.55722
Step #2500, epoch #625, avg. train loss: 398.36374
Step #2600, epoch #650, avg. train loss: 389.23547
Step #2700, epoch #675, avg. train loss: 385.52637
Step #2800, epoch #700, avg. train loss: 376.32657
Step #2900, epoch #725, avg. train loss: 370.16949
Step #3000, epoch #750, avg. train loss: 364.08875
Step #3100, epoch #775, avg. train loss: 356.13617
Step #3200, epoch #800, avg. train loss: 351.47778
Step #3300, epoch #825, avg. train loss: 345.58661
Step #3400, epoch #850, avg. train loss: 337.73590
Step #3500, epoch #875, avg. train loss: 333.38220
Step #3600, epoch #900, avg. train loss: 328.88583
Step #3700, epoch #925, avg. train loss: 323.23370
Step #3800, epoch #950, avg. train loss: 318.93274
Step #3900, epoch #975, avg. train loss: 312.50589
Step #4000, epoch #1000, avg. train loss: 308.44302
Step #4100, epoch #1025, avg. train loss: 303.04950
Step #4200, epoch #1050, avg. train loss: 298.57355
Step #4300, epoch #1075, avg. train loss: 295.76697
Step #4400, epoch #1100, avg. train loss: 289.37103
Step #4500, epoch #1125, avg. train loss: 285.23029
Step #4600, epoch #1150, avg. train loss: 283.82635
Step #4700, epoch #1175, avg. train loss: 277.74814
Step #4800, epoch #1200, avg. train loss: 275.18201
Step #4900, epoch #1225, avg. train loss: 271.51669
Step #5000, epoch #1250, avg. train loss: 270.27216
Step #5100, epoch #1275, avg. train loss: 266.40561
Step #5200, epoch #1300, avg. train loss: 262.32098
Step #5300, epoch #1325, avg. train loss: 259.08154
Step #5400, epoch #1350, avg. train loss: 255.80202
Step #5500, epoch #1375, avg. train loss: 253.09753
Step #5600, epoch #1400, avg. train loss: 250.42802
Step #5700, epoch #1425, avg. train loss: 247.49364
Step #5800, epoch #1450, avg. train loss: 244.37033
Step #5900, epoch #1475, avg. train loss: 242.28511
Step #6000, epoch #1500, avg. train loss: 239.62694
Step #6100, epoch #1525, avg. train loss: 239.41681
Step #6200, epoch #1550, avg. train loss: 235.21297
Step #6300, epoch #1575, avg. train loss: 233.37270
Step #6400, epoch #1600, avg. train loss: 231.91666
Step #6500, epoch #1625, avg. train loss: 229.04385
Step #6600, epoch #1650, avg. train loss: 226.95807
Step #6700, epoch #1675, avg. train loss: 225.16080
Step #6800, epoch #1700, avg. train loss: 224.06752
Step #6900, epoch #1725, avg. train loss: 222.88643
Step #7000, epoch #1750, avg. train loss: 222.68958
Step #7100, epoch #1775, avg. train loss: 218.80415
Step #7200, epoch #1800, avg. train loss: 217.69476
Step #7300, epoch #1825, avg. train loss: 215.99521
Step #7400, epoch #1850, avg. train loss: 215.40031
Step #7500, epoch #1875, avg. train loss: 213.95398
Step #7600, epoch #1900, avg. train loss: 211.21507
Step #7700, epoch #1925, avg. train loss: 210.96933
Step #7800, epoch #1950, avg. train loss: 210.04848
Step #7900, epoch #1975, avg. train loss: 209.31573
Step #8000, epoch #2000, avg. train loss: 206.95108
Step #8100, epoch #2025, avg. train loss: 205.77814
Step #8200, epoch #2050, avg. train loss: 206.25299
Step #8300, epoch #2075, avg. train loss: 203.49556
Step #8400, epoch #2100, avg. train loss: 203.72905
Step #8500, epoch #2125, avg. train loss: 202.31081
Step #8600, epoch #2150, avg. train loss: 200.49898
Step #8700, epoch #2175, avg. train loss: 201.96010
Step #8800, epoch #2200, avg. train loss: 198.83539
Step #8900, epoch #2225, avg. train loss: 198.92339
Step #9000, epoch #2250, avg. train loss: 197.12045
Step #9100, epoch #2275, avg. train loss: 195.10085
Step #9200, epoch #2300, avg. train loss: 197.46477
Step #9300, epoch #2325, avg. train loss: 193.84659
Step #9400, epoch #2350, avg. train loss: 194.40692
Step #9500, epoch #2375, avg. train loss: 194.40584
Step #9600, epoch #2400, avg. train loss: 193.55266
Step #9700, epoch #2425, avg. train loss: 191.71379
Step #9800, epoch #2450, avg. train loss: 192.89362
Step #9900, epoch #2475, avg. train loss: 191.62624
Step #10000, epoch #2500, avg. train loss: 189.63858
Step #10100, epoch #2525, avg. train loss: 187.97034
Step #10200, epoch #2550, avg. train loss: 190.27638
Step #10300, epoch #2575, avg. train loss: 188.30620
Step #10400, epoch #2600, avg. train loss: 187.69882
Step #10500, epoch #2625, avg. train loss: 186.48442
Step #10600, epoch #2650, avg. train loss: 184.28299
Step #10700, epoch #2675, avg. train loss: 185.69208
Step #10800, epoch #2700, avg. train loss: 183.79051
Step #10900, epoch #2725, avg. train loss: 183.32011
Step #11000, epoch #2750, avg. train loss: 183.46161
Step #11100, epoch #2775, avg. train loss: 183.03767
Step #11200, epoch #2800, avg. train loss: 182.39606
Step #11300, epoch #2825, avg. train loss: 181.42120
Step #11400, epoch #2850, avg. train loss: 180.63055
Step #11500, epoch #2875, avg. train loss: 180.64172
Step #11600, epoch #2900, avg. train loss: 178.50110
Step #11700, epoch #2925, avg. train loss: 179.16684
Step #11800, epoch #2950, avg. train loss: 178.56026
Step #11900, epoch #2975, avg. train loss: 177.03084
Step #12000, epoch #3000, avg. train loss: 177.72481
Step #12100, epoch #3025, avg. train loss: 176.41176
Step #12200, epoch #3050, avg. train loss: 177.39510
Step #12300, epoch #3075, avg. train loss: 175.62868
Step #12400, epoch #3100, avg. train loss: 174.46597
Step #12500, epoch #3125, avg. train loss: 173.00809
Step #12600, epoch #3150, avg. train loss: 174.36264
Step #12700, epoch #3175, avg. train loss: 172.53311
Step #12800, epoch #3200, avg. train loss: 173.01158
Step #12900, epoch #3225, avg. train loss: 172.63176
Step #13000, epoch #3250, avg. train loss: 171.35834
Step #13100, epoch #3275, avg. train loss: 171.13045
Step #13200, epoch #3300, avg. train loss: 171.10400
Step #13300, epoch #3325, avg. train loss: 169.10524
Step #13400, epoch #3350, avg. train loss: 169.69022
Step #13500, epoch #3375, avg. train loss: 168.18408
Step #13600, epoch #3400, avg. train loss: 168.46898
Step #13700, epoch #3425, avg. train loss: 168.20369
Step #13800, epoch #3450, avg. train loss: 167.92747
Step #13900, epoch #3475, avg. train loss: 168.32800
Step #14000, epoch #3500, avg. train loss: 165.75172
Step #14100, epoch #3525, avg. train loss: 166.70650
Step #14200, epoch #3550, avg. train loss: 165.50116
Step #14300, epoch #3575, avg. train loss: 164.87198
Step #14400, epoch #3600, avg. train loss: 164.17857
Step #14500, epoch #3625, avg. train loss: 164.76285
Step #14600, epoch #3650, avg. train loss: 163.55789
Step #14700, epoch #3675, avg. train loss: 163.28006
Step #14800, epoch #3700, avg. train loss: 161.76683
Step #14900, epoch #3725, avg. train loss: 162.39783
Step #15000, epoch #3750, avg. train loss: 161.36249
Step #15100, epoch #3775, avg. train loss: 161.80318
Step #15200, epoch #3800, avg. train loss: 160.94194
Step #15300, epoch #3825, avg. train loss: 160.28822
Step #15400, epoch #3850, avg. train loss: 159.91589
Step #15500, epoch #3875, avg. train loss: 161.53114
Step #15600, epoch #3900, avg. train loss: 158.60478
Step #15700, epoch #3925, avg. train loss: 158.77423
Step #15800, epoch #3950, avg. train loss: 156.85931
Step #15900, epoch #3975, avg. train loss: 157.99931
Step #16000, epoch #4000, avg. train loss: 158.28604
Step #16100, epoch #4025, avg. train loss: 155.70898
Step #16200, epoch #4050, avg. train loss: 157.15881
Step #16300, epoch #4075, avg. train loss: 155.93619
Step #16400, epoch #4100, avg. train loss: 156.83986
Step #16500, epoch #4125, avg. train loss: 153.88130
Step #16600, epoch #4150, avg. train loss: 153.99982
Step #16700, epoch #4175, avg. train loss: 155.09485
Step #16800, epoch #4200, avg. train loss: 153.69727
Step #16900, epoch #4225, avg. train loss: 153.95079
Step #17000, epoch #4250, avg. train loss: 153.77484
Step #17100, epoch #4275, avg. train loss: 153.16365
Step #17200, epoch #4300, avg. train loss: 151.80595
Step #17300, epoch #4325, avg. train loss: 151.30820
Step #17400, epoch #4350, avg. train loss: 152.51698
Step #17500, epoch #4375, avg. train loss: 151.32201
Step #17600, epoch #4400, avg. train loss: 151.02007
Step #17700, epoch #4425, avg. train loss: 150.98364
Step #17800, epoch #4450, avg. train loss: 150.73138
Step #17900, epoch #4475, avg. train loss: 149.51189
Step #18000, epoch #4500, avg. train loss: 150.02583
Step #18100, epoch #4525, avg. train loss: 149.09694
Step #18200, epoch #4550, avg. train loss: 149.12701
Step #18300, epoch #4575, avg. train loss: 147.92294
Step #18400, epoch #4600, avg. train loss: 149.03528
Step #18500, epoch #4625, avg. train loss: 148.97569
Step #18600, epoch #4650, avg. train loss: 147.79637
Step #18700, epoch #4675, avg. train loss: 147.01640
Step #18800, epoch #4700, avg. train loss: 148.09634
Step #18900, epoch #4725, avg. train loss: 148.29010
Step #19000, epoch #4750, avg. train loss: 146.11212
Step #19100, epoch #4775, avg. train loss: 146.01869
Step #19200, epoch #4800, avg. train loss: 145.52609
Step #19300, epoch #4825, avg. train loss: 147.65005
Step #19400, epoch #4850, avg. train loss: 145.95348
Step #19500, epoch #4875, avg. train loss: 146.13866
Step #19600, epoch #4900, avg. train loss: 144.57492
Step #19700, epoch #4925, avg. train loss: 143.92554
Step #19800, epoch #4950, avg. train loss: 143.89482
Step #19900, epoch #4975, avg. train loss: 143.82628
Step #20000, epoch #5000, avg. train loss: 143.60280
Step #20100, epoch #5025, avg. train loss: 143.03882
Step #20200, epoch #5050, avg. train loss: 142.90767
Step #20300, epoch #5075, avg. train loss: 143.75580
Step #20400, epoch #5100, avg. train loss: 143.67865
Step #20500, epoch #5125, avg. train loss: 143.29277
Step #20600, epoch #5150, avg. train loss: 141.57285
Step #20700, epoch #5175, avg. train loss: 141.22145
Step #20800, epoch #5200, avg. train loss: 142.66718
Step #20900, epoch #5225, avg. train loss: 139.35527
Step #21000, epoch #5250, avg. train loss: 139.57681
Step #21100, epoch #5275, avg. train loss: 139.56793
Step #21200, epoch #5300, avg. train loss: 139.60277
Step #21300, epoch #5325, avg. train loss: 138.71713
Step #21400, epoch #5350, avg. train loss: 139.97226
Step #21500, epoch #5375, avg. train loss: 140.13625
Step #21600, epoch #5400, avg. train loss: 139.01071
Step #21700, epoch #5425, avg. train loss: 138.11191
Step #21800, epoch #5450, avg. train loss: 138.44998
Step #21900, epoch #5475, avg. train loss: 137.30785
Step #22000, epoch #5500, avg. train loss: 137.32028
Step #22100, epoch #5525, avg. train loss: 136.57439
Step #22200, epoch #5550, avg. train loss: 137.34541
Step #22300, epoch #5575, avg. train loss: 136.32762
Step #22400, epoch #5600, avg. train loss: 136.44293
Step #22500, epoch #5625, avg. train loss: 136.93274
Step #22600, epoch #5650, avg. train loss: 134.75186
Step #22700, epoch #5675, avg. train loss: 136.33302
Step #22800, epoch #5700, avg. train loss: 135.76968
Step #22900, epoch #5725, avg. train loss: 135.71767
Step #23000, epoch #5750, avg. train loss: 135.67952
Step #23100, epoch #5775, avg. train loss: 135.82558
Step #23200, epoch #5800, avg. train loss: 134.51550
Step #23300, epoch #5825, avg. train loss: 134.53477
Step #23400, epoch #5850, avg. train loss: 133.93391
Step #23500, epoch #5875, avg. train loss: 133.26740
Step #23600, epoch #5900, avg. train loss: 132.50044
Step #23700, epoch #5925, avg. train loss: 132.11018
Step #23800, epoch #5950, avg. train loss: 132.28650
Step #23900, epoch #5975, avg. train loss: 132.66553
Step #24000, epoch #6000, avg. train loss: 131.88857
Step #24100, epoch #6025, avg. train loss: 132.02419
Step #24200, epoch #6050, avg. train loss: 131.94281
Step #24300, epoch #6075, avg. train loss: 131.32428
Step #24400, epoch #6100, avg. train loss: 130.68442
Step #24500, epoch #6125, avg. train loss: 130.79036
Step #24600, epoch #6150, avg. train loss: 130.66777
Step #24700, epoch #6175, avg. train loss: 130.56821
Step #24800, epoch #6200, avg. train loss: 129.06111
Step #24900, epoch #6225, avg. train loss: 128.60971
Step #25000, epoch #6250, avg. train loss: 127.90011
Step #25100, epoch #6275, avg. train loss: 128.23477
Step #25200, epoch #6300, avg. train loss: 126.99606
Step #25300, epoch #6325, avg. train loss: 126.50196
Step #25400, epoch #6350, avg. train loss: 127.08691
Step #25500, epoch #6375, avg. train loss: 126.89670
Step #25600, epoch #6400, avg. train loss: 126.87180
Step #25700, epoch #6425, avg. train loss: 125.67732
Step #25800, epoch #6450, avg. train loss: 125.99989
Step #25900, epoch #6475, avg. train loss: 126.94444
Step #26000, epoch #6500, avg. train loss: 125.16441
Step #26100, epoch #6525, avg. train loss: 125.69783
Step #26200, epoch #6550, avg. train loss: 123.56291
Step #26300, epoch #6575, avg. train loss: 123.40298
Step #26400, epoch #6600, avg. train loss: 123.58801
Step #26500, epoch #6625, avg. train loss: 122.69287
Step #26600, epoch #6650, avg. train loss: 123.72319
Step #26700, epoch #6675, avg. train loss: 123.05116
Step #26800, epoch #6700, avg. train loss: 122.35065
Step #26900, epoch #6725, avg. train loss: 124.04962
Step #27000, epoch #6750, avg. train loss: 122.07202
Step #27100, epoch #6775, avg. train loss: 122.23064
Step #27200, epoch #6800, avg. train loss: 122.62276
Step #27300, epoch #6825, avg. train loss: 121.18580
Step #27400, epoch #6850, avg. train loss: 121.75433
Step #27500, epoch #6875, avg. train loss: 121.63410
Step #27600, epoch #6900, avg. train loss: 120.97070
Step #27700, epoch #6925, avg. train loss: 120.33315
Step #27800, epoch #6950, avg. train loss: 120.21546
Step #27900, epoch #6975, avg. train loss: 121.63285
Step #28000, epoch #7000, avg. train loss: 120.76559
Step #28100, epoch #7025, avg. train loss: 119.90044
Step #28200, epoch #7050, avg. train loss: 121.08485
Step #28300, epoch #7075, avg. train loss: 119.26590
Step #28400, epoch #7100, avg. train loss: 119.76900
Step #28500, epoch #7125, avg. train loss: 118.72301
Step #28600, epoch #7150, avg. train loss: 119.73759
Step #28700, epoch #7175, avg. train loss: 119.16592
Step #28800, epoch #7200, avg. train loss: 119.18204
Step #28900, epoch #7225, avg. train loss: 119.11251
Step #29000, epoch #7250, avg. train loss: 119.80444
Step #29100, epoch #7275, avg. train loss: 118.59129
Step #29200, epoch #7300, avg. train loss: 117.20927
Step #29300, epoch #7325, avg. train loss: 117.43545
Step #29400, epoch #7350, avg. train loss: 118.26366
Step #29500, epoch #7375, avg. train loss: 116.26242
Step #29600, epoch #7400, avg. train loss: 117.27544
Step #29700, epoch #7425, avg. train loss: 117.73640
Step #29800, epoch #7450, avg. train loss: 117.00244
Step #29900, epoch #7475, avg. train loss: 117.29578
Step #30000, epoch #7500, avg. train loss: 117.58694
Step #30100, epoch #7525, avg. train loss: 116.98193
Step #30200, epoch #7550, avg. train loss: 115.89481
Step #30300, epoch #7575, avg. train loss: 116.33801
Step #30400, epoch #7600, avg. train loss: 116.83910
Step #30500, epoch #7625, avg. train loss: 115.74123
Step #30600, epoch #7650, avg. train loss: 114.74637
Step #30700, epoch #7675, avg. train loss: 114.64705
Step #30800, epoch #7700, avg. train loss: 115.02351
Step #30900, epoch #7725, avg. train loss: 114.71961
Step #31000, epoch #7750, avg. train loss: 115.24413
Step #31100, epoch #7775, avg. train loss: 115.32450
Step #31200, epoch #7800, avg. train loss: 114.47176
Step #31300, epoch #7825, avg. train loss: 113.96276
Step #31400, epoch #7850, avg. train loss: 113.60617
Step #31500, epoch #7875, avg. train loss: 114.30585
Step #31600, epoch #7900, avg. train loss: 113.78590
Step #31700, epoch #7925, avg. train loss: 113.35143
Step #31800, epoch #7950, avg. train loss: 113.61594
Step #31900, epoch #7975, avg. train loss: 113.36810
Step #32000, epoch #8000, avg. train loss: 114.02179
Step #32100, epoch #8025, avg. train loss: 113.08671
Step #32200, epoch #8050, avg. train loss: 113.40765
Step #32300, epoch #8075, avg. train loss: 112.45787
Step #32400, epoch #8100, avg. train loss: 112.21423
Step #32500, epoch #8125, avg. train loss: 112.08694
Step #32600, epoch #8150, avg. train loss: 112.84388
Step #32700, epoch #8175, avg. train loss: 112.35041
Step #32800, epoch #8200, avg. train loss: 112.83656
Step #32900, epoch #8225, avg. train loss: 112.18546
Step #33000, epoch #8250, avg. train loss: 112.37656
Step #33100, epoch #8275, avg. train loss: 111.85793
Step #33200, epoch #8300, avg. train loss: 112.45348
Step #33300, epoch #8325, avg. train loss: 111.95971
Step #33400, epoch #8350, avg. train loss: 112.03705
Step #33500, epoch #8375, avg. train loss: 111.43039
Step #33600, epoch #8400, avg. train loss: 111.53356
Step #33700, epoch #8425, avg. train loss: 110.47317
Step #33800, epoch #8450, avg. train loss: 111.37928
Step #33900, epoch #8475, avg. train loss: 110.56107
Step #34000, epoch #8500, avg. train loss: 110.25726
Step #34100, epoch #8525, avg. train loss: 110.38678
Step #34200, epoch #8550, avg. train loss: 110.63829
Step #34300, epoch #8575, avg. train loss: 109.97068
Step #34400, epoch #8600, avg. train loss: 110.91617
Step #34500, epoch #8625, avg. train loss: 110.30782
Step #34600, epoch #8650, avg. train loss: 110.17867
Step #34700, epoch #8675, avg. train loss: 109.68415
Step #34800, epoch #8700, avg. train loss: 109.25402
Step #34900, epoch #8725, avg. train loss: 109.91939
Step #35000, epoch #8750, avg. train loss: 108.38168
Step #35100, epoch #8775, avg. train loss: 108.93024
Step #35200, epoch #8800, avg. train loss: 109.51620
Step #35300, epoch #8825, avg. train loss: 109.02205
Step #35400, epoch #8850, avg. train loss: 108.91599
Step #35500, epoch #8875, avg. train loss: 108.62505
Step #35600, epoch #8900, avg. train loss: 109.88200
Step #35700, epoch #8925, avg. train loss: 109.61555
Step #35800, epoch #8950, avg. train loss: 108.52662
Step #35900, epoch #8975, avg. train loss: 108.76253
Step #36000, epoch #9000, avg. train loss: 108.14119
Step #36100, epoch #9025, avg. train loss: 108.34032
Step #36200, epoch #9050, avg. train loss: 107.95235
Step #36300, epoch #9075, avg. train loss: 107.81795
Step #36400, epoch #9100, avg. train loss: 107.40094
Step #36500, epoch #9125, avg. train loss: 108.01363
Step #36600, epoch #9150, avg. train loss: 107.63937
Step #36700, epoch #9175, avg. train loss: 107.87326
Step #36800, epoch #9200, avg. train loss: 107.50186
Step #36900, epoch #9225, avg. train loss: 108.68342
Step #37000, epoch #9250, avg. train loss: 108.17242
Step #37100, epoch #9275, avg. train loss: 106.72423
Step #37200, epoch #9300, avg. train loss: 107.04308
Step #37300, epoch #9325, avg. train loss: 106.18624
Step #37400, epoch #9350, avg. train loss: 107.57010
Step #37500, epoch #9375, avg. train loss: 107.13644
Step #37600, epoch #9400, avg. train loss: 106.51333
Step #37700, epoch #9425, avg. train loss: 107.04919
Step #37800, epoch #9450, avg. train loss: 107.83661
Step #37900, epoch #9475, avg. train loss: 106.21429
Step #38000, epoch #9500, avg. train loss: 105.89809
Step #38100, epoch #9525, avg. train loss: 107.21922
Step #38200, epoch #9550, avg. train loss: 106.02399
Step #38300, epoch #9575, avg. train loss: 106.40563
Step #38400, epoch #9600, avg. train loss: 106.09521
Step #38500, epoch #9625, avg. train loss: 104.66814
Step #38600, epoch #9650, avg. train loss: 105.59141
Step #38700, epoch #9675, avg. train loss: 104.46255
Step #38800, epoch #9700, avg. train loss: 105.19933
Step #38900, epoch #9725, avg. train loss: 105.22510
Step #39000, epoch #9750, avg. train loss: 105.06892
Step #39100, epoch #9775, avg. train loss: 104.96674
Step #39200, epoch #9800, avg. train loss: 104.90218
Step #39300, epoch #9825, avg. train loss: 104.77261
Step #39400, epoch #9850, avg. train loss: 104.66743
Step #39500, epoch #9875, avg. train loss: 104.93759
Step #39600, epoch #9900, avg. train loss: 104.43670
Step #39700, epoch #9925, avg. train loss: 104.60664
Step #39800, epoch #9950, avg. train loss: 104.22980
Step #39900, epoch #9975, avg. train loss: 105.08838
Step #40000, epoch #10000, avg. train loss: 103.31798
Step #40100, epoch #10025, avg. train loss: 104.30099
Step #40200, epoch #10050, avg. train loss: 103.93258
Step #40300, epoch #10075, avg. train loss: 104.89422
Step #40400, epoch #10100, avg. train loss: 103.59658
Step #40500, epoch #10125, avg. train loss: 104.32747
Step #40600, epoch #10150, avg. train loss: 103.10488
Step #40700, epoch #10175, avg. train loss: 103.57010
Step #40800, epoch #10200, avg. train loss: 103.08695
Step #40900, epoch #10225, avg. train loss: 103.27852
Step #41000, epoch #10250, avg. train loss: 103.98364
Step #41100, epoch #10275, avg. train loss: 103.47513
Step #41200, epoch #10300, avg. train loss: 102.60506
Step #41300, epoch #10325, avg. train loss: 104.20268
Step #41400, epoch #10350, avg. train loss: 103.22636
Step #41500, epoch #10375, avg. train loss: 102.83073
Step #41600, epoch #10400, avg. train loss: 103.35209
Step #41700, epoch #10425, avg. train loss: 103.20190
Step #41800, epoch #10450, avg. train loss: 103.19441
Step #41900, epoch #10475, avg. train loss: 103.72624
Step #42000, epoch #10500, avg. train loss: 102.07475
Step #42100, epoch #10525, avg. train loss: 102.70590
Step #42200, epoch #10550, avg. train loss: 103.67241
Step #42300, epoch #10575, avg. train loss: 102.59718
Step #42400, epoch #10600, avg. train loss: 101.88747
Step #42500, epoch #10625, avg. train loss: 101.70645
Step #42600, epoch #10650, avg. train loss: 102.22070
Step #42700, epoch #10675, avg. train loss: 102.72733
Step #42800, epoch #10700, avg. train loss: 101.81205
Step #42900, epoch #10725, avg. train loss: 101.72329
Step #43000, epoch #10750, avg. train loss: 101.40014
Step #43100, epoch #10775, avg. train loss: 101.60911
Step #43200, epoch #10800, avg. train loss: 101.67024
Step #43300, epoch #10825, avg. train loss: 102.36997
Step #43400, epoch #10850, avg. train loss: 101.13986
Step #43500, epoch #10875, avg. train loss: 101.69986
Step #43600, epoch #10900, avg. train loss: 100.84488
Step #43700, epoch #10925, avg. train loss: 101.35703
Step #43800, epoch #10950, avg. train loss: 101.31504
Step #43900, epoch #10975, avg. train loss: 101.73969
Step #44000, epoch #11000, avg. train loss: 101.32209
Step #44100, epoch #11025, avg. train loss: 101.32495
Step #44200, epoch #11050, avg. train loss: 100.52298
Step #44300, epoch #11075, avg. train loss: 101.22343
Step #44400, epoch #11100, avg. train loss: 101.83582
Step #44500, epoch #11125, avg. train loss: 100.85041
Step #44600, epoch #11150, avg. train loss: 102.63437
Step #44700, epoch #11175, avg. train loss: 100.42900
Step #44800, epoch #11200, avg. train loss: 100.45180
Step #44900, epoch #11225, avg. train loss: 101.23797
Step #45000, epoch #11250, avg. train loss: 101.25843
Step #45100, epoch #11275, avg. train loss: 100.79151
Step #45200, epoch #11300, avg. train loss: 101.01425
Step #45300, epoch #11325, avg. train loss: 100.32787
Step #45400, epoch #11350, avg. train loss: 100.79747
Step #45500, epoch #11375, avg. train loss: 100.94985
Step #45600, epoch #11400, avg. train loss: 100.71490
Step #45700, epoch #11425, avg. train loss: 99.17588
Step #45800, epoch #11450, avg. train loss: 99.78642
Step #45900, epoch #11475, avg. train loss: 100.45322
Step #46000, epoch #11500, avg. train loss: 100.33839
Step #46100, epoch #11525, avg. train loss: 101.56233
Step #46200, epoch #11550, avg. train loss: 100.33099
Step #46300, epoch #11575, avg. train loss: 100.20605
Step #46400, epoch #11600, avg. train loss: 99.90045
Step #46500, epoch #11625, avg. train loss: 99.94360
Step #46600, epoch #11650, avg. train loss: 100.17143
Step #46700, epoch #11675, avg. train loss: 99.85763
Step #46800, epoch #11700, avg. train loss: 98.94346
Step #46900, epoch #11725, avg. train loss: 99.12387
Step #47000, epoch #11750, avg. train loss: 98.59631
Step #47100, epoch #11775, avg. train loss: 99.60547
Step #47200, epoch #11800, avg. train loss: 98.86517
Step #47300, epoch #11825, avg. train loss: 99.66671
Step #47400, epoch #11850, avg. train loss: 99.74767
Step #47500, epoch #11875, avg. train loss: 99.39695
Step #47600, epoch #11900, avg. train loss: 99.54726
Step #47700, epoch #11925, avg. train loss: 99.19661
Step #47800, epoch #11950, avg. train loss: 98.91961
Step #47900, epoch #11975, avg. train loss: 99.01354
Step #48000, epoch #12000, avg. train loss: 99.26183
Step #48100, epoch #12025, avg. train loss: 99.65548
Step #48200, epoch #12050, avg. train loss: 99.16788
Step #48300, epoch #12075, avg. train loss: 99.66449
Step #48400, epoch #12100, avg. train loss: 98.80768
Step #48500, epoch #12125, avg. train loss: 98.90768
Step #48600, epoch #12150, avg. train loss: 98.84883
Step #48700, epoch #12175, avg. train loss: 99.13609
Step #48800, epoch #12200, avg. train loss: 98.58719
Step #48900, epoch #12225, avg. train loss: 98.96067
Step #49000, epoch #12250, avg. train loss: 98.73061
Step #49100, epoch #12275, avg. train loss: 98.53304
Step #49200, epoch #12300, avg. train loss: 97.93489
Step #49300, epoch #12325, avg. train loss: 98.35491
Step #49400, epoch #12350, avg. train loss: 98.16897
Step #49500, epoch #12375, avg. train loss: 98.02085
Step #49600, epoch #12400, avg. train loss: 98.51538
Step #49700, epoch #12425, avg. train loss: 98.76161
Step #49800, epoch #12450, avg. train loss: 98.21274
Step #49900, epoch #12475, avg. train loss: 98.17931
Step #50000, epoch #12500, avg. train loss: 97.71651
Step #50100, epoch #12525, avg. train loss: 97.68137
Step #50200, epoch #12550, avg. train loss: 98.10030
Step #50300, epoch #12575, avg. train loss: 97.94169
Step #50400, epoch #12600, avg. train loss: 97.77425
Step #50500, epoch #12625, avg. train loss: 96.78813
Step #50600, epoch #12650, avg. train loss: 97.48827
Step #50700, epoch #12675, avg. train loss: 98.26260
Step #50800, epoch #12700, avg. train loss: 97.99799
Step #50900, epoch #12725, avg. train loss: 98.28168
Step #51000, epoch #12750, avg. train loss: 98.23298
Step #51100, epoch #12775, avg. train loss: 98.01143
Step #51200, epoch #12800, avg. train loss: 97.65903
Step #51300, epoch #12825, avg. train loss: 97.88254
Step #51400, epoch #12850, avg. train loss: 97.10213
Step #51500, epoch #12875, avg. train loss: 97.14243
Step #51600, epoch #12900, avg. train loss: 97.57459
Step #51700, epoch #12925, avg. train loss: 97.37663
Step #51800, epoch #12950, avg. train loss: 98.04880
Step #51900, epoch #12975, avg. train loss: 96.51437
Step #52000, epoch #13000, avg. train loss: 97.00764
Step #52100, epoch #13025, avg. train loss: 97.13445
Step #52200, epoch #13050, avg. train loss: 97.41512
Step #52300, epoch #13075, avg. train loss: 96.89007
Step #52400, epoch #13100, avg. train loss: 96.38750
Step #52500, epoch #13125, avg. train loss: 97.73563
Step #52600, epoch #13150, avg. train loss: 97.45479
Step #52700, epoch #13175, avg. train loss: 96.76556
Step #52800, epoch #13200, avg. train loss: 97.44203
Step #52900, epoch #13225, avg. train loss: 96.53038
Step #53000, epoch #13250, avg. train loss: 96.24986
Step #53100, epoch #13275, avg. train loss: 95.80859
Step #53200, epoch #13300, avg. train loss: 95.28251
Step #53300, epoch #13325, avg. train loss: 96.61530
Step #53400, epoch #13350, avg. train loss: 97.49048
Step #53500, epoch #13375, avg. train loss: 96.32969
Step #53600, epoch #13400, avg. train loss: 96.46069
Step #53700, epoch #13425, avg. train loss: 96.34445
Step #53800, epoch #13450, avg. train loss: 97.70205
Step #53900, epoch #13475, avg. train loss: 97.11845
Step #54000, epoch #13500, avg. train loss: 97.09615
Step #54100, epoch #13525, avg. train loss: 96.62775
Step #54200, epoch #13550, avg. train loss: 96.26649
Step #54300, epoch #13575, avg. train loss: 96.35649
Step #54400, epoch #13600, avg. train loss: 96.62189
Step #54500, epoch #13625, avg. train loss: 96.27890
Step #54600, epoch #13650, avg. train loss: 95.68429
Step #54700, epoch #13675, avg. train loss: 95.82271
Step #54800, epoch #13700, avg. train loss: 95.90629
Step #54900, epoch #13725, avg. train loss: 96.53713
Step #55000, epoch #13750, avg. train loss: 96.31919
Step #55100, epoch #13775, avg. train loss: 96.36838
Step #55200, epoch #13800, avg. train loss: 96.08858
Step #55300, epoch #13825, avg. train loss: 96.52329
Step #55400, epoch #13850, avg. train loss: 95.97392
Step #55500, epoch #13875, avg. train loss: 95.66323
Step #55600, epoch #13900, avg. train loss: 95.27256
Step #55700, epoch #13925, avg. train loss: 94.94456
Step #55800, epoch #13950, avg. train loss: 95.11704
Step #55900, epoch #13975, avg. train loss: 95.26492
Step #56000, epoch #14000, avg. train loss: 95.52286
Step #56100, epoch #14025, avg. train loss: 95.91525
Step #56200, epoch #14050, avg. train loss: 95.66176
Step #56300, epoch #14075, avg. train loss: 95.60860
Step #56400, epoch #14100, avg. train loss: 95.54021
Step #56500, epoch #14125, avg. train loss: 95.91805
Step #56600, epoch #14150, avg. train loss: 94.95529
Step #56700, epoch #14175, avg. train loss: 95.95090
Step #56800, epoch #14200, avg. train loss: 96.42371
Step #56900, epoch #14225, avg. train loss: 95.42512
Step #57000, epoch #14250, avg. train loss: 94.93269
Step #57100, epoch #14275, avg. train loss: 94.90570
Step #57200, epoch #14300, avg. train loss: 95.28149
Step #57300, epoch #14325, avg. train loss: 95.38898
Step #57400, epoch #14350, avg. train loss: 96.28336
Step #57500, epoch #14375, avg. train loss: 95.94756
Step #57600, epoch #14400, avg. train loss: 94.50118
Step #57700, epoch #14425, avg. train loss: 95.72680
Step #57800, epoch #14450, avg. train loss: 95.45971
Step #57900, epoch #14475, avg. train loss: 95.09677
Step #58000, epoch #14500, avg. train loss: 94.53027
Step #58100, epoch #14525, avg. train loss: 95.39497
Step #58200, epoch #14550, avg. train loss: 95.20710
Step #58300, epoch #14575, avg. train loss: 95.55693
Step #58400, epoch #14600, avg. train loss: 94.88685
Step #58500, epoch #14625, avg. train loss: 94.75918
Step #58600, epoch #14650, avg. train loss: 93.89707
Step #58700, epoch #14675, avg. train loss: 95.23049
Step #58800, epoch #14700, avg. train loss: 95.89545
Step #58900, epoch #14725, avg. train loss: 94.95191
Step #59000, epoch #14750, avg. train loss: 93.97137
Step #59100, epoch #14775, avg. train loss: 93.79411
Step #59200, epoch #14800, avg. train loss: 95.32621
Step #59300, epoch #14825, avg. train loss: 95.55630
Step #59400, epoch #14850, avg. train loss: 95.12753
Step #59500, epoch #14875, avg. train loss: 94.65585
Step #59600, epoch #14900, avg. train loss: 95.22115
Step #59700, epoch #14925, avg. train loss: 95.53090
Step #59800, epoch #14950, avg. train loss: 94.53089
Step #59900, epoch #14975, avg. train loss: 93.58102
Step #60000, epoch #15000, avg. train loss: 93.72334
Step #60100, epoch #15025, avg. train loss: 94.73219
Step #60200, epoch #15050, avg. train loss: 95.30740
Step #60300, epoch #15075, avg. train loss: 93.64524
Step #60400, epoch #15100, avg. train loss: 94.16339
Step #60500, epoch #15125, avg. train loss: 94.25311
Step #60600, epoch #15150, avg. train loss: 94.62975
Step #60700, epoch #15175, avg. train loss: 95.00949
Step #60800, epoch #15200, avg. train loss: 94.73206
Step #60900, epoch #15225, avg. train loss: 94.80518
Step #61000, epoch #15250, avg. train loss: 94.59164
Step #61100, epoch #15275, avg. train loss: 95.21254
Step #61200, epoch #15300, avg. train loss: 94.20821
Step #61300, epoch #15325, avg. train loss: 94.26628
Step #61400, epoch #15350, avg. train loss: 94.83890
Step #61500, epoch #15375, avg. train loss: 95.01678
Step #61600, epoch #15400, avg. train loss: 94.05806
Step #61700, epoch #15425, avg. train loss: 93.52034
Step #61800, epoch #15450, avg. train loss: 93.47269
Step #61900, epoch #15475, avg. train loss: 94.30793
Step #62000, epoch #15500, avg. train loss: 93.88989
Step #62100, epoch #15525, avg. train loss: 95.14366
Step #62200, epoch #15550, avg. train loss: 94.42654
Step #62300, epoch #15575, avg. train loss: 93.61308
Step #62400, epoch #15600, avg. train loss: 93.73852
Step #62500, epoch #15625, avg. train loss: 94.38374
Step #62600, epoch #15650, avg. train loss: 93.27359
Step #62700, epoch #15675, avg. train loss: 93.79729
Step #62800, epoch #15700, avg. train loss: 93.58015
Step #62900, epoch #15725, avg. train loss: 94.13909
Step #63000, epoch #15750, avg. train loss: 94.68160
Step #63100, epoch #15775, avg. train loss: 94.54990
Step #63200, epoch #15800, avg. train loss: 94.14746
Step #63300, epoch #15825, avg. train loss: 94.37996
Step #63400, epoch #15850, avg. train loss: 94.99232
Step #63500, epoch #15875, avg. train loss: 93.54015
Step #63600, epoch #15900, avg. train loss: 94.63552
Step #63700, epoch #15925, avg. train loss: 93.30782
Step #63800, epoch #15950, avg. train loss: 94.28452
Step #63900, epoch #15975, avg. train loss: 94.69982
Step #64000, epoch #16000, avg. train loss: 93.78365
Step #64100, epoch #16025, avg. train loss: 94.04983
Step #64200, epoch #16050, avg. train loss: 93.30235
Step #64300, epoch #16075, avg. train loss: 93.76367
Step #64400, epoch #16100, avg. train loss: 93.02200
Step #64500, epoch #16125, avg. train loss: 94.15622
Step #64600, epoch #16150, avg. train loss: 93.51939
Step #64700, epoch #16175, avg. train loss: 93.54314
Step #64800, epoch #16200, avg. train loss: 93.68906
Step #64900, epoch #16225, avg. train loss: 93.36369
Step #65000, epoch #16250, avg. train loss: 94.04771
Step #65100, epoch #16275, avg. train loss: 93.49258
Step #65200, epoch #16300, avg. train loss: 93.53327
Step #65300, epoch #16325, avg. train loss: 93.83154
Step #65400, epoch #16350, avg. train loss: 93.58798
Step #65500, epoch #16375, avg. train loss: 94.12886
Step #65600, epoch #16400, avg. train loss: 93.17934
Step #65700, epoch #16425, avg. train loss: 92.65539
Step #65800, epoch #16450, avg. train loss: 93.32568
Step #65900, epoch #16475, avg. train loss: 93.44831
Step #66000, epoch #16500, avg. train loss: 92.94030
Step #66100, epoch #16525, avg. train loss: 94.03131
Step #66200, epoch #16550, avg. train loss: 93.69615
Step #66300, epoch #16575, avg. train loss: 93.28749
Step #66400, epoch #16600, avg. train loss: 94.05126
Step #66500, epoch #16625, avg. train loss: 92.07038
Step #66600, epoch #16650, avg. train loss: 93.00171
Step #66700, epoch #16675, avg. train loss: 93.45361
Step #66800, epoch #16700, avg. train loss: 94.42341
Step #66900, epoch #16725, avg. train loss: 93.97778
Step #67000, epoch #16750, avg. train loss: 93.31244
Step #67100, epoch #16775, avg. train loss: 92.81854
Step #67200, epoch #16800, avg. train loss: 93.16869
Step #67300, epoch #16825, avg. train loss: 92.85242
Step #67400, epoch #16850, avg. train loss: 92.29190
Step #67500, epoch #16875, avg. train loss: 92.87891
Step #67600, epoch #16900, avg. train loss: 92.34402
Step #67700, epoch #16925, avg. train loss: 92.67912
Step #67800, epoch #16950, avg. train loss: 92.98386
Step #67900, epoch #16975, avg. train loss: 93.37320
Step #68000, epoch #17000, avg. train loss: 93.09255
Step #68100, epoch #17025, avg. train loss: 92.88013
Step #68200, epoch #17050, avg. train loss: 92.88258
Step #68300, epoch #17075, avg. train loss: 92.28204
Step #68400, epoch #17100, avg. train loss: 92.06218
Step #68500, epoch #17125, avg. train loss: 91.75594
Step #68600, epoch #17150, avg. train loss: 92.72105
Step #68700, epoch #17175, avg. train loss: 93.02833
Step #68800, epoch #17200, avg. train loss: 93.33872
Step #68900, epoch #17225, avg. train loss: 92.80595
Step #69000, epoch #17250, avg. train loss: 92.73449
Step #69100, epoch #17275, avg. train loss: 94.01877
Step #69200, epoch #17300, avg. train loss: 93.28185
Step #69300, epoch #17325, avg. train loss: 92.37305
Step #69400, epoch #17350, avg. train loss: 92.61454
Step #69500, epoch #17375, avg. train loss: 92.93128
Step #69600, epoch #17400, avg. train loss: 92.58036
Step #69700, epoch #17425, avg. train loss: 93.42310
Step #69800, epoch #17450, avg. train loss: 93.30463
Step #69900, epoch #17475, avg. train loss: 93.29562
Step #70000, epoch #17500, avg. train loss: 92.94651
Step #70100, epoch #17525, avg. train loss: 92.02180
Step #70200, epoch #17550, avg. train loss: 92.65136
Step #70300, epoch #17575, avg. train loss: 92.51378
Step #70400, epoch #17600, avg. train loss: 92.62779
Step #70500, epoch #17625, avg. train loss: 92.43363
Step #70600, epoch #17650, avg. train loss: 93.54450
Step #70700, epoch #17675, avg. train loss: 92.28474
Step #70800, epoch #17700, avg. train loss: 93.23374
Step #70900, epoch #17725, avg. train loss: 92.20615
Step #71000, epoch #17750, avg. train loss: 91.95100
Step #71100, epoch #17775, avg. train loss: 91.21565
Step #71200, epoch #17800, avg. train loss: 92.59760
Step #71300, epoch #17825, avg. train loss: 92.67152
Step #71400, epoch #17850, avg. train loss: 93.16388
Step #71500, epoch #17875, avg. train loss: 92.49742
Step #71600, epoch #17900, avg. train loss: 93.43303
Step #71700, epoch #17925, avg. train loss: 92.83462
Step #71800, epoch #17950, avg. train loss: 91.88572
Step #71900, epoch #17975, avg. train loss: 92.54957
Step #72000, epoch #18000, avg. train loss: 91.69451
Step #72100, epoch #18025, avg. train loss: 92.86513
Step #72200, epoch #18050, avg. train loss: 91.34280
Step #72300, epoch #18075, avg. train loss: 91.08169
Step #72400, epoch #18100, avg. train loss: 92.93761
Step #72500, epoch #18125, avg. train loss: 90.91196
Step #72600, epoch #18150, avg. train loss: 92.21703
Step #72700, epoch #18175, avg. train loss: 92.07195
Step #72800, epoch #18200, avg. train loss: 92.31619
Step #72900, epoch #18225, avg. train loss: 91.38110
Step #73000, epoch #18250, avg. train loss: 91.45066
Step #73100, epoch #18275, avg. train loss: 91.55476
Step #73200, epoch #18300, avg. train loss: 92.29209
Step #73300, epoch #18325, avg. train loss: 91.29552
Step #73400, epoch #18350, avg. train loss: 91.49010
Step #73500, epoch #18375, avg. train loss: 91.81075
Step #73600, epoch #18400, avg. train loss: 92.54784
Step #73700, epoch #18425, avg. train loss: 91.25189
Step #73800, epoch #18450, avg. train loss: 92.68177
Step #73900, epoch #18475, avg. train loss: 92.17694
Step #74000, epoch #18500, avg. train loss: 91.49453
Step #74100, epoch #18525, avg. train loss: 92.47179
Step #74200, epoch #18550, avg. train loss: 91.72868
Step #74300, epoch #18575, avg. train loss: 91.86451
Step #74400, epoch #18600, avg. train loss: 91.99490
Step #74500, epoch #18625, avg. train loss: 91.45390
Step #74600, epoch #18650, avg. train loss: 91.32366
Step #74700, epoch #18675, avg. train loss: 92.77245
Step #74800, epoch #18700, avg. train loss: 91.47162
Step #74900, epoch #18725, avg. train loss: 92.05240
Step #75000, epoch #18750, avg. train loss: 91.74991
Step #75100, epoch #18775, avg. train loss: 92.14846
Step #75200, epoch #18800, avg. train loss: 91.89520
Step #75300, epoch #18825, avg. train loss: 90.66762
Step #75400, epoch #18850, avg. train loss: 91.76991
Step #75500, epoch #18875, avg. train loss: 91.11777
Step #75600, epoch #18900, avg. train loss: 92.25903
Step #75700, epoch #18925, avg. train loss: 91.55905
Step #75800, epoch #18950, avg. train loss: 91.93594
Step #75900, epoch #18975, avg. train loss: 92.07432
Step #76000, epoch #19000, avg. train loss: 91.61848
Step #76100, epoch #19025, avg. train loss: 91.54385
Step #76200, epoch #19050, avg. train loss: 91.76266
Step #76300, epoch #19075, avg. train loss: 91.16635
Step #76400, epoch #19100, avg. train loss: 91.74595
Step #76500, epoch #19125, avg. train loss: 91.89037
Step #76600, epoch #19150, avg. train loss: 91.94586
Step #76700, epoch #19175, avg. train loss: 90.73855
Step #76800, epoch #19200, avg. train loss: 91.43950
Step #76900, epoch #19225, avg. train loss: 91.16179
Step #77000, epoch #19250, avg. train loss: 91.13490
Step #77100, epoch #19275, avg. train loss: 90.70071
Step #77200, epoch #19300, avg. train loss: 91.02396
Step #77300, epoch #19325, avg. train loss: 92.70779
Step #77400, epoch #19350, avg. train loss: 92.23625
Step #77500, epoch #19375, avg. train loss: 91.37665
Step #77600, epoch #19400, avg. train loss: 91.63415
Step #77700, epoch #19425, avg. train loss: 91.12979
Step #77800, epoch #19450, avg. train loss: 91.38263
Step #77900, epoch #19475, avg. train loss: 91.53226
Step #78000, epoch #19500, avg. train loss: 91.98975
Step #78100, epoch #19525, avg. train loss: 91.55232
Step #78200, epoch #19550, avg. train loss: 91.22116
Step #78300, epoch #19575, avg. train loss: 91.52026
Step #78400, epoch #19600, avg. train loss: 91.09608
Step #78500, epoch #19625, avg. train loss: 91.34309
Step #78600, epoch #19650, avg. train loss: 91.38903
Step #78700, epoch #19675, avg. train loss: 91.23843
Step #78800, epoch #19700, avg. train loss: 90.17938
Step #78900, epoch #19725, avg. train loss: 91.36533
Step #79000, epoch #19750, avg. train loss: 90.66113
Step #79100, epoch #19775, avg. train loss: 90.70274
Step #79200, epoch #19800, avg. train loss: 91.65577
Step #79300, epoch #19825, avg. train loss: 90.48012
Step #79400, epoch #19850, avg. train loss: 90.95672
Step #79500, epoch #19875, avg. train loss: 90.96899
Step #79600, epoch #19900, avg. train loss: 91.05925
Step #79700, epoch #19925, avg. train loss: 90.94162
Step #79800, epoch #19950, avg. train loss: 91.52651
Step #79900, epoch #19975, avg. train loss: 91.42800
Step #80000, epoch #20000, avg. train loss: 91.48646
Step #80100, epoch #20025, avg. train loss: 91.04397
Step #80200, epoch #20050, avg. train loss: 90.89324
Step #80300, epoch #20075, avg. train loss: 90.72886
Step #80400, epoch #20100, avg. train loss: 91.30737
Step #80500, epoch #20125, avg. train loss: 90.04807
Step #80600, epoch #20150, avg. train loss: 91.23148
Step #80700, epoch #20175, avg. train loss: 91.33427
Step #80800, epoch #20200, avg. train loss: 90.66149
Step #80900, epoch #20225, avg. train loss: 90.47382
Step #81000, epoch #20250, avg. train loss: 91.12290
Step #81100, epoch #20275, avg. train loss: 90.74599
Step #81200, epoch #20300, avg. train loss: 90.90304
Step #81300, epoch #20325, avg. train loss: 90.29397
Step #81400, epoch #20350, avg. train loss: 90.02686
Step #81500, epoch #20375, avg. train loss: 90.81723
Step #81600, epoch #20400, avg. train loss: 90.78751
Step #81700, epoch #20425, avg. train loss: 90.98001
Step #81800, epoch #20450, avg. train loss: 90.46780
Step #81900, epoch #20475, avg. train loss: 90.42017
Step #82000, epoch #20500, avg. train loss: 91.15493
Step #82100, epoch #20525, avg. train loss: 90.32590
Step #82200, epoch #20550, avg. train loss: 90.67127
Step #82300, epoch #20575, avg. train loss: 90.86879
Step #82400, epoch #20600, avg. train loss: 91.12123
Step #82500, epoch #20625, avg. train loss: 90.49728
Step #82600, epoch #20650, avg. train loss: 90.89125
Step #82700, epoch #20675, avg. train loss: 90.26731
Step #82800, epoch #20700, avg. train loss: 90.38184
Step #82900, epoch #20725, avg. train loss: 91.81851
Step #83000, epoch #20750, avg. train loss: 90.13037
Step #83100, epoch #20775, avg. train loss: 90.93934
Step #83200, epoch #20800, avg. train loss: 90.17393
Step #83300, epoch #20825, avg. train loss: 90.31919
Step #83400, epoch #20850, avg. train loss: 90.89680
Step #83500, epoch #20875, avg. train loss: 91.23731
Step #83600, epoch #20900, avg. train loss: 91.24005
Step #83700, epoch #20925, avg. train loss: 90.65064
Step #83800, epoch #20950, avg. train loss: 90.15576
Step #83900, epoch #20975, avg. train loss: 90.40329
Step #84000, epoch #21000, avg. train loss: 90.46882
Step #84100, epoch #21025, avg. train loss: 90.66068
Step #84200, epoch #21050, avg. train loss: 90.05362
Step #84300, epoch #21075, avg. train loss: 92.02126
Step #84400, epoch #21100, avg. train loss: 90.33131
Step #84500, epoch #21125, avg. train loss: 90.62840
Step #84600, epoch #21150, avg. train loss: 90.33192
Step #84700, epoch #21175, avg. train loss: 90.60720
Step #84800, epoch #21200, avg. train loss: 90.11341
Step #84900, epoch #21225, avg. train loss: 89.57168
Step #85000, epoch #21250, avg. train loss: 90.45399
Step #85100, epoch #21275, avg. train loss: 89.43838
Step #85200, epoch #21300, avg. train loss: 90.35035
Step #85300, epoch #21325, avg. train loss: 90.49363
Step #85400, epoch #21350, avg. train loss: 89.85754
Step #85500, epoch #21375, avg. train loss: 90.12631
Step #85600, epoch #21400, avg. train loss: 90.37663
Step #85700, epoch #21425, avg. train loss: 90.68579
Step #85800, epoch #21450, avg. train loss: 89.69003
Step #85900, epoch #21475, avg. train loss: 89.80856
Step #86000, epoch #21500, avg. train loss: 90.03781
Step #86100, epoch #21525, avg. train loss: 90.37859
Step #86200, epoch #21550, avg. train loss: 89.48032
Step #86300, epoch #21575, avg. train loss: 90.15932
Step #86400, epoch #21600, avg. train loss: 91.17636
Step #86500, epoch #21625, avg. train loss: 89.75422
Step #86600, epoch #21650, avg. train loss: 90.03072
Step #86700, epoch #21675, avg. train loss: 90.30166
Step #86800, epoch #21700, avg. train loss: 90.83122
Step #86900, epoch #21725, avg. train loss: 89.88264
Step #87000, epoch #21750, avg. train loss: 90.49328
Step #87100, epoch #21775, avg. train loss: 89.75883
Step #87200, epoch #21800, avg. train loss: 90.09233
Step #87300, epoch #21825, avg. train loss: 90.65475
Step #87400, epoch #21850, avg. train loss: 89.11709
Step #87500, epoch #21875, avg. train loss: 90.94790
Step #87600, epoch #21900, avg. train loss: 90.37225
Step #87700, epoch #21925, avg. train loss: 89.94734
Step #87800, epoch #21950, avg. train loss: 90.65785
Step #87900, epoch #21975, avg. train loss: 90.37367
Step #88000, epoch #22000, avg. train loss: 90.13028
Step #88100, epoch #22025, avg. train loss: 90.06045
Step #88200, epoch #22050, avg. train loss: 90.50704
Step #88300, epoch #22075, avg. train loss: 90.82735
Step #88400, epoch #22100, avg. train loss: 90.57878
Step #88500, epoch #22125, avg. train loss: 90.35525
Step #88600, epoch #22150, avg. train loss: 90.30529
Step #88700, epoch #22175, avg. train loss: 90.33305
Step #88800, epoch #22200, avg. train loss: 90.16743
Step #88900, epoch #22225, avg. train loss: 89.17265
Step #89000, epoch #22250, avg. train loss: 89.46677
Step #89100, epoch #22275, avg. train loss: 90.44096
Step #89200, epoch #22300, avg. train loss: 89.51872
Step #89300, epoch #22325, avg. train loss: 89.16644
Step #89400, epoch #22350, avg. train loss: 89.75296
Step #89500, epoch #22375, avg. train loss: 90.02976
Step #89600, epoch #22400, avg. train loss: 89.30875
Step #89700, epoch #22425, avg. train loss: 89.40527
Step #89800, epoch #22450, avg. train loss: 89.71464
Step #89900, epoch #22475, avg. train loss: 90.43730
Step #90000, epoch #22500, avg. train loss: 89.79043
Step #90100, epoch #22525, avg. train loss: 89.16822
Step #90200, epoch #22550, avg. train loss: 88.89227
Step #90300, epoch #22575, avg. train loss: 89.29692
Step #90400, epoch #22600, avg. train loss: 90.58867
Step #90500, epoch #22625, avg. train loss: 90.23208
Step #90600, epoch #22650, avg. train loss: 89.55168
Step #90700, epoch #22675, avg. train loss: 89.66254
Step #90800, epoch #22700, avg. train loss: 89.77956
Step #90900, epoch #22725, avg. train loss: 89.95129
Step #91000, epoch #22750, avg. train loss: 88.85899
Step #91100, epoch #22775, avg. train loss: 89.99647
Step #91200, epoch #22800, avg. train loss: 89.68498
Step #91300, epoch #22825, avg. train loss: 90.27274
Step #91400, epoch #22850, avg. train loss: 89.49337
Step #91500, epoch #22875, avg. train loss: 89.49745
Step #91600, epoch #22900, avg. train loss: 89.13336
Step #91700, epoch #22925, avg. train loss: 89.18603
Step #91800, epoch #22950, avg. train loss: 89.66338
Step #91900, epoch #22975, avg. train loss: 89.61761
Step #92000, epoch #23000, avg. train loss: 89.25998
Step #92100, epoch #23025, avg. train loss: 89.37531
Step #92200, epoch #23050, avg. train loss: 89.73215
Step #92300, epoch #23075, avg. train loss: 89.08196
Step #92400, epoch #23100, avg. train loss: 89.89471
Step #92500, epoch #23125, avg. train loss: 90.05014
Step #92600, epoch #23150, avg. train loss: 90.01375
Step #92700, epoch #23175, avg. train loss: 88.60469
Step #92800, epoch #23200, avg. train loss: 89.49055
Step #92900, epoch #23225, avg. train loss: 89.25041
Step #93000, epoch #23250, avg. train loss: 89.95992
Step #93100, epoch #23275, avg. train loss: 89.42606
Step #93200, epoch #23300, avg. train loss: 89.91041
Step #93300, epoch #23325, avg. train loss: 89.78490
Step #93400, epoch #23350, avg. train loss: 90.21676
Step #93500, epoch #23375, avg. train loss: 89.25020
Step #93600, epoch #23400, avg. train loss: 89.54708
Step #93700, epoch #23425, avg. train loss: 90.18597
Step #93800, epoch #23450, avg. train loss: 90.33696
Step #93900, epoch #23475, avg. train loss: 89.20563
Step #94000, epoch #23500, avg. train loss: 89.97756
Step #94100, epoch #23525, avg. train loss: 89.17400
Step #94200, epoch #23550, avg. train loss: 89.96030
Step #94300, epoch #23575, avg. train loss: 88.85086
Step #94400, epoch #23600, avg. train loss: 89.38022
Step #94500, epoch #23625, avg. train loss: 89.52464
Step #94600, epoch #23650, avg. train loss: 90.03325
Step #94700, epoch #23675, avg. train loss: 88.64748
Step #94800, epoch #23700, avg. train loss: 89.45696
Step #94900, epoch #23725, avg. train loss: 88.96732
Step #95000, epoch #23750, avg. train loss: 89.23309
Step #95100, epoch #23775, avg. train loss: 89.47929
Step #95200, epoch #23800, avg. train loss: 88.44527
Step #95300, epoch #23825, avg. train loss: 89.75143
Step #95400, epoch #23850, avg. train loss: 89.73163
Step #95500, epoch #23875, avg. train loss: 89.74473
Step #95600, epoch #23900, avg. train loss: 89.11561
Step #95700, epoch #23925, avg. train loss: 89.82552
Step #95800, epoch #23950, avg. train loss: 89.11211
Step #95900, epoch #23975, avg. train loss: 88.93981
Step #96000, epoch #24000, avg. train loss: 90.53604
Step #96100, epoch #24025, avg. train loss: 89.25397
Step #96200, epoch #24050, avg. train loss: 90.35583
Step #96300, epoch #24075, avg. train loss: 89.25250
Step #96400, epoch #24100, avg. train loss: 89.22559
Step #96500, epoch #24125, avg. train loss: 88.98322
Step #96600, epoch #24150, avg. train loss: 89.15417
Step #96700, epoch #24175, avg. train loss: 89.46304
Step #96800, epoch #24200, avg. train loss: 88.91103
Step #96900, epoch #24225, avg. train loss: 88.70592
Step #97000, epoch #24250, avg. train loss: 90.04321
Step #97100, epoch #24275, avg. train loss: 89.55989
Step #97200, epoch #24300, avg. train loss: 88.43668
Step #97300, epoch #24325, avg. train loss: 88.84643
Step #97400, epoch #24350, avg. train loss: 89.03501
Step #97500, epoch #24375, avg. train loss: 88.82042
Step #97600, epoch #24400, avg. train loss: 89.53537
Step #97700, epoch #24425, avg. train loss: 89.37415
Step #97800, epoch #24450, avg. train loss: 89.16958
Step #97900, epoch #24475, avg. train loss: 88.69037
Step #98000, epoch #24500, avg. train loss: 88.92139
Step #98100, epoch #24525, avg. train loss: 89.53637
Step #98200, epoch #24550, avg. train loss: 88.75857
Step #98300, epoch #24575, avg. train loss: 88.24907
Step #98400, epoch #24600, avg. train loss: 88.55241
Step #98500, epoch #24625, avg. train loss: 88.92274
Step #98600, epoch #24650, avg. train loss: 89.65628
Step #98700, epoch #24675, avg. train loss: 88.82646
Step #98800, epoch #24700, avg. train loss: 88.47216
Step #98900, epoch #24725, avg. train loss: 88.25572
Step #99000, epoch #24750, avg. train loss: 88.79336
Step #99100, epoch #24775, avg. train loss: 88.71722
Step #99200, epoch #24800, avg. train loss: 88.51884
Step #99300, epoch #24825, avg. train loss: 89.54639
Step #99400, epoch #24850, avg. train loss: 89.14561
Step #99500, epoch #24875, avg. train loss: 89.81443
Step #99600, epoch #24900, avg. train loss: 88.99536
Step #99700, epoch #24925, avg. train loss: 89.02435
Step #99800, epoch #24950, avg. train loss: 88.96719
Step #99900, epoch #24975, avg. train loss: 88.40991
Step #100000, epoch #25000, avg. train loss: 89.22095
Step #100100, epoch #25025, avg. train loss: 88.77738
Step #100200, epoch #25050, avg. train loss: 88.00149
Step #100300, epoch #25075, avg. train loss: 89.08823
Step #100400, epoch #25100, avg. train loss: 89.23742
Step #100500, epoch #25125, avg. train loss: 89.59287
Step #100600, epoch #25150, avg. train loss: 89.03011
Step #100700, epoch #25175, avg. train loss: 89.54781
Step #100800, epoch #25200, avg. train loss: 88.81034
Step #100900, epoch #25225, avg. train loss: 89.67648
Step #101000, epoch #25250, avg. train loss: 89.33609
Step #101100, epoch #25275, avg. train loss: 89.07181
Step #101200, epoch #25300, avg. train loss: 89.19131
Step #101300, epoch #25325, avg. train loss: 88.07949
Step #101400, epoch #25350, avg. train loss: 88.33050
Step #101500, epoch #25375, avg. train loss: 88.80839
Step #101600, epoch #25400, avg. train loss: 87.96955
Step #101700, epoch #25425, avg. train loss: 89.11014
Step #101800, epoch #25450, avg. train loss: 89.42570
Step #101900, epoch #25475, avg. train loss: 88.37192
Step #102000, epoch #25500, avg. train loss: 87.99073
Step #102100, epoch #25525, avg. train loss: 88.42161
Step #102200, epoch #25550, avg. train loss: 88.31294
Step #102300, epoch #25575, avg. train loss: 88.76649
Step #102400, epoch #25600, avg. train loss: 88.46903
Step #102500, epoch #25625, avg. train loss: 89.53351
Step #102600, epoch #25650, avg. train loss: 88.74979
Step #102700, epoch #25675, avg. train loss: 88.38724
Step #102800, epoch #25700, avg. train loss: 89.07461
Step #102900, epoch #25725, avg. train loss: 88.59030
Step #103000, epoch #25750, avg. train loss: 89.41019
Step #103100, epoch #25775, avg. train loss: 89.08269
Step #103200, epoch #25800, avg. train loss: 88.46939
Step #103300, epoch #25825, avg. train loss: 87.90510
Step #103400, epoch #25850, avg. train loss: 88.59013
Step #103500, epoch #25875, avg. train loss: 89.33017
Step #103600, epoch #25900, avg. train loss: 88.20296
Step #103700, epoch #25925, avg. train loss: 89.10497
Step #103800, epoch #25950, avg. train loss: 87.43992
Step #103900, epoch #25975, avg. train loss: 88.80280
Step #104000, epoch #26000, avg. train loss: 88.17812
Step #104100, epoch #26025, avg. train loss: 87.39946
Step #104200, epoch #26050, avg. train loss: 88.52798
Step #104300, epoch #26075, avg. train loss: 88.81829
Step #104400, epoch #26100, avg. train loss: 88.33501
Step #104500, epoch #26125, avg. train loss: 88.25129
Step #104600, epoch #26150, avg. train loss: 89.09880
Step #104700, epoch #26175, avg. train loss: 88.09908
Step #104800, epoch #26200, avg. train loss: 87.68234
Step #104900, epoch #26225, avg. train loss: 88.16266
Step #105000, epoch #26250, avg. train loss: 88.16173
Step #105100, epoch #26275, avg. train loss: 88.08210
Step #105200, epoch #26300, avg. train loss: 88.66437
Step #105300, epoch #26325, avg. train loss: 88.34878
Step #105400, epoch #26350, avg. train loss: 88.41448
Step #105500, epoch #26375, avg. train loss: 88.64773
Step #105600, epoch #26400, avg. train loss: 89.01072
Step #105700, epoch #26425, avg. train loss: 88.77833
Step #105800, epoch #26450, avg. train loss: 87.84217
Step #105900, epoch #26475, avg. train loss: 87.79202
Step #106000, epoch #26500, avg. train loss: 89.41792
Step #106100, epoch #26525, avg. train loss: 87.78241
Step #106200, epoch #26550, avg. train loss: 88.13852
Step #106300, epoch #26575, avg. train loss: 88.89840
Step #106400, epoch #26600, avg. train loss: 88.01453
Step #106500, epoch #26625, avg. train loss: 87.96363
Step #106600, epoch #26650, avg. train loss: 88.43555
Step #106700, epoch #26675, avg. train loss: 88.47966
Step #106800, epoch #26700, avg. train loss: 87.85117
Step #106900, epoch #26725, avg. train loss: 88.52287
Step #107000, epoch #26750, avg. train loss: 88.68017
Step #107100, epoch #26775, avg. train loss: 89.24902
Step #107200, epoch #26800, avg. train loss: 87.99819
Step #107300, epoch #26825, avg. train loss: 87.74635
Step #107400, epoch #26850, avg. train loss: 88.57217
Step #107500, epoch #26875, avg. train loss: 88.66035
Step #107600, epoch #26900, avg. train loss: 87.61631
Step #107700, epoch #26925, avg. train loss: 87.61751
Step #107800, epoch #26950, avg. train loss: 88.62514
Step #107900, epoch #26975, avg. train loss: 88.28661
Step #108000, epoch #27000, avg. train loss: 88.97817
Step #108100, epoch #27025, avg. train loss: 87.47910
Step #108200, epoch #27050, avg. train loss: 87.94947
Step #108300, epoch #27075, avg. train loss: 86.81519
Step #108400, epoch #27100, avg. train loss: 88.78885
Step #108500, epoch #27125, avg. train loss: 88.17629
Step #108600, epoch #27150, avg. train loss: 89.12804
Step #108700, epoch #27175, avg. train loss: 87.66622
Step #108800, epoch #27200, avg. train loss: 88.04266
Step #108900, epoch #27225, avg. train loss: 88.10991
Step #109000, epoch #27250, avg. train loss: 87.42323
Step #109100, epoch #27275, avg. train loss: 87.20012
Step #109200, epoch #27300, avg. train loss: 87.93735
Step #109300, epoch #27325, avg. train loss: 87.22814
Step #109400, epoch #27350, avg. train loss: 88.46853
Step #109500, epoch #27375, avg. train loss: 87.67009
Step #109600, epoch #27400, avg. train loss: 87.50816
Step #109700, epoch #27425, avg. train loss: 87.31898
Step #109800, epoch #27450, avg. train loss: 88.04501
Step #109900, epoch #27475, avg. train loss: 88.15614
Step #110000, epoch #27500, avg. train loss: 88.64133
Step #110100, epoch #27525, avg. train loss: 88.38097
Step #110200, epoch #27550, avg. train loss: 87.53378
Step #110300, epoch #27575, avg. train loss: 87.90237
Step #110400, epoch #27600, avg. train loss: 87.97621
Step #110500, epoch #27625, avg. train loss: 87.24784
Step #110600, epoch #27650, avg. train loss: 88.28718
Step #110700, epoch #27675, avg. train loss: 87.95046
Step #110800, epoch #27700, avg. train loss: 88.29803
Step #110900, epoch #27725, avg. train loss: 88.40331
Step #111000, epoch #27750, avg. train loss: 87.77145
Step #111100, epoch #27775, avg. train loss: 87.15074
Step #111200, epoch #27800, avg. train loss: 88.81687
Step #111300, epoch #27825, avg. train loss: 88.01098
Step #111400, epoch #27850, avg. train loss: 87.51405
Step #111500, epoch #27875, avg. train loss: 88.02435
Step #111600, epoch #27900, avg. train loss: 87.94753
Step #111700, epoch #27925, avg. train loss: 88.36112
Step #111800, epoch #27950, avg. train loss: 87.63347
Step #111900, epoch #27975, avg. train loss: 87.91417
Step #112000, epoch #28000, avg. train loss: 89.67134
Step #112100, epoch #28025, avg. train loss: 87.51406
Step #112200, epoch #28050, avg. train loss: 87.85564
Step #112300, epoch #28075, avg. train loss: 88.14956
Step #112400, epoch #28100, avg. train loss: 87.42204
Step #112500, epoch #28125, avg. train loss: 87.21893
Step #112600, epoch #28150, avg. train loss: 88.35800
Step #112700, epoch #28175, avg. train loss: 87.12583
Step #112800, epoch #28200, avg. train loss: 86.76406
Step #112900, epoch #28225, avg. train loss: 88.19053
Step #113000, epoch #28250, avg. train loss: 87.72230
Step #113100, epoch #28275, avg. train loss: 88.47037
Step #113200, epoch #28300, avg. train loss: 87.18498
Step #113300, epoch #28325, avg. train loss: 87.51680
Step #113400, epoch #28350, avg. train loss: 87.60745
Step #113500, epoch #28375, avg. train loss: 87.46693
Step #113600, epoch #28400, avg. train loss: 88.03693
Step #113700, epoch #28425, avg. train loss: 86.96127
Step #113800, epoch #28450, avg. train loss: 87.76004
Step #113900, epoch #28475, avg. train loss: 87.42221
Step #114000, epoch #28500, avg. train loss: 87.65859
Step #114100, epoch #28525, avg. train loss: 87.56976
Step #114200, epoch #28550, avg. train loss: 87.16396
Step #114300, epoch #28575, avg. train loss: 88.39000
Step #114400, epoch #28600, avg. train loss: 87.22829
Step #114500, epoch #28625, avg. train loss: 87.68378
Step #114600, epoch #28650, avg. train loss: 87.15974
Step #114700, epoch #28675, avg. train loss: 87.81551
Step #114800, epoch #28700, avg. train loss: 87.86458
Step #114900, epoch #28725, avg. train loss: 87.54683
Step #115000, epoch #28750, avg. train loss: 87.85269
Step #115100, epoch #28775, avg. train loss: 88.18143
Step #115200, epoch #28800, avg. train loss: 88.33105
Step #115300, epoch #28825, avg. train loss: 87.40188
Step #115400, epoch #28850, avg. train loss: 87.27686
Step #115500, epoch #28875, avg. train loss: 87.94476
Step #115600, epoch #28900, avg. train loss: 87.12124
Step #115700, epoch #28925, avg. train loss: 87.14002
Step #115800, epoch #28950, avg. train loss: 86.80428
Step #115900, epoch #28975, avg. train loss: 87.91798
Step #116000, epoch #29000, avg. train loss: 87.60839
Step #116100, epoch #29025, avg. train loss: 87.43931
Step #116200, epoch #29050, avg. train loss: 87.44499
Step #116300, epoch #29075, avg. train loss: 87.53869
Step #116400, epoch #29100, avg. train loss: 88.25642
Step #116500, epoch #29125, avg. train loss: 88.00405
Step #116600, epoch #29150, avg. train loss: 86.65830
Step #116700, epoch #29175, avg. train loss: 87.85110
Step #116800, epoch #29200, avg. train loss: 86.95679
Step #116900, epoch #29225, avg. train loss: 87.50500
Step #117000, epoch #29250, avg. train loss: 88.19489
Step #117100, epoch #29275, avg. train loss: 86.97598
Step #117200, epoch #29300, avg. train loss: 88.10229
Step #117300, epoch #29325, avg. train loss: 87.62585
Step #117400, epoch #29350, avg. train loss: 87.01912
Step #117500, epoch #29375, avg. train loss: 87.53815
Step #117600, epoch #29400, avg. train loss: 87.76493
Step #117700, epoch #29425, avg. train loss: 87.81556
Step #117800, epoch #29450, avg. train loss: 87.41312
Step #117900, epoch #29475, avg. train loss: 87.18613
Step #118000, epoch #29500, avg. train loss: 87.66064
Step #118100, epoch #29525, avg. train loss: 88.03491
Step #118200, epoch #29550, avg. train loss: 87.01070
Step #118300, epoch #29575, avg. train loss: 86.98763
Step #118400, epoch #29600, avg. train loss: 87.85546
Step #118500, epoch #29625, avg. train loss: 87.58368
Step #118600, epoch #29650, avg. train loss: 86.74602
Step #118700, epoch #29675, avg. train loss: 88.37756
Step #118800, epoch #29700, avg. train loss: 87.16531
Step #118900, epoch #29725, avg. train loss: 86.33098
Step #119000, epoch #29750, avg. train loss: 86.99574
Step #119100, epoch #29775, avg. train loss: 88.17392
Step #119200, epoch #29800, avg. train loss: 86.66636
Step #119300, epoch #29825, avg. train loss: 87.50331
Step #119400, epoch #29850, avg. train loss: 87.01852
Step #119500, epoch #29875, avg. train loss: 87.73332
Step #119600, epoch #29900, avg. train loss: 86.63578
Step #119700, epoch #29925, avg. train loss: 86.60414
Step #119800, epoch #29950, avg. train loss: 87.25123
Step #119900, epoch #29975, avg. train loss: 87.13675
Step #120000, epoch #30000, avg. train loss: 87.11485
Step #120100, epoch #30025, avg. train loss: 87.18135
Step #120200, epoch #30050, avg. train loss: 88.27557
Step #120300, epoch #30075, avg. train loss: 87.54349
Step #120400, epoch #30100, avg. train loss: 86.86158
Step #120500, epoch #30125, avg. train loss: 86.60356
Step #120600, epoch #30150, avg. train loss: 86.77749
Step #120700, epoch #30175, avg. train loss: 86.62785
Step #120800, epoch #30200, avg. train loss: 86.86966
Step #120900, epoch #30225, avg. train loss: 87.49283
Step #121000, epoch #30250, avg. train loss: 87.56062
Step #121100, epoch #30275, avg. train loss: 87.94534
Step #121200, epoch #30300, avg. train loss: 87.56070
Step #121300, epoch #30325, avg. train loss: 87.80202
Step #121400, epoch #30350, avg. train loss: 87.09916
Step #121500, epoch #30375, avg. train loss: 88.02719
Step #121600, epoch #30400, avg. train loss: 86.47800
Step #121700, epoch #30425, avg. train loss: 87.48521
Step #121800, epoch #30450, avg. train loss: 86.04605
Step #121900, epoch #30475, avg. train loss: 86.83712
Step #122000, epoch #30500, avg. train loss: 87.26321
Step #122100, epoch #30525, avg. train loss: 86.66757
Step #122200, epoch #30550, avg. train loss: 86.19638
Step #122300, epoch #30575, avg. train loss: 87.29723
Step #122400, epoch #30600, avg. train loss: 86.85731
Step #122500, epoch #30625, avg. train loss: 86.23121
Step #122600, epoch #30650, avg. train loss: 87.43794
Step #122700, epoch #30675, avg. train loss: 86.89997
Step #122800, epoch #30700, avg. train loss: 86.86980
Step #122900, epoch #30725, avg. train loss: 87.11742
Step #123000, epoch #30750, avg. train loss: 87.39256
Step #123100, epoch #30775, avg. train loss: 86.88131
Step #123200, epoch #30800, avg. train loss: 87.58160
Step #123300, epoch #30825, avg. train loss: 86.60160
Step #123400, epoch #30850, avg. train loss: 87.65147
Step #123500, epoch #30875, avg. train loss: 87.16197
Step #123600, epoch #30900, avg. train loss: 86.71298
Step #123700, epoch #30925, avg. train loss: 86.70595
Step #123800, epoch #30950, avg. train loss: 87.92375
Step #123900, epoch #30975, avg. train loss: 86.70412
Step #124000, epoch #31000, avg. train loss: 87.61788
Step #124100, epoch #31025, avg. train loss: 86.56461
Step #124200, epoch #31050, avg. train loss: 87.06183
Step #124300, epoch #31075, avg. train loss: 87.67670
Step #124400, epoch #31100, avg. train loss: 86.17082
Step #124500, epoch #31125, avg. train loss: 86.80878
Step #124600, epoch #31150, avg. train loss: 87.12383
Step #124700, epoch #31175, avg. train loss: 86.20411
Step #124800, epoch #31200, avg. train loss: 86.60893
Step #124900, epoch #31225, avg. train loss: 86.78239
Step #125000, epoch #31250, avg. train loss: 87.09373
Step #125100, epoch #31275, avg. train loss: 87.31261
Step #125200, epoch #31300, avg. train loss: 87.74872
Step #125300, epoch #31325, avg. train loss: 87.17728
Step #125400, epoch #31350, avg. train loss: 87.16550
Step #125500, epoch #31375, avg. train loss: 85.89289
Step #125600, epoch #31400, avg. train loss: 86.97798
Step #125700, epoch #31425, avg. train loss: 86.81795
Step #125800, epoch #31450, avg. train loss: 86.34041
Step #125900, epoch #31475, avg. train loss: 86.56123
Step #126000, epoch #31500, avg. train loss: 87.02714
Step #126100, epoch #31525, avg. train loss: 86.05601
Step #126200, epoch #31550, avg. train loss: 86.68653
Step #126300, epoch #31575, avg. train loss: 86.64951
Step #126400, epoch #31600, avg. train loss: 87.61667
Step #126500, epoch #31625, avg. train loss: 86.37569
Step #126600, epoch #31650, avg. train loss: 85.85110
Step #126700, epoch #31675, avg. train loss: 87.30613
Step #126800, epoch #31700, avg. train loss: 86.79381
Step #126900, epoch #31725, avg. train loss: 86.60174
Step #127000, epoch #31750, avg. train loss: 85.98994
Step #127100, epoch #31775, avg. train loss: 86.44916
Step #127200, epoch #31800, avg. train loss: 86.63815
Step #127300, epoch #31825, avg. train loss: 86.42980
Step #127400, epoch #31850, avg. train loss: 86.71347
Step #127500, epoch #31875, avg. train loss: 86.65134
Step #127600, epoch #31900, avg. train loss: 86.60603
Step #127700, epoch #31925, avg. train loss: 86.51887
Step #127800, epoch #31950, avg. train loss: 86.83884
Step #127900, epoch #31975, avg. train loss: 86.58263
Step #128000, epoch #32000, avg. train loss: 86.46310
Step #128100, epoch #32025, avg. train loss: 86.70930
Step #128200, epoch #32050, avg. train loss: 86.31643
Step #128300, epoch #32075, avg. train loss: 86.28613
Step #128400, epoch #32100, avg. train loss: 86.06838
Step #128500, epoch #32125, avg. train loss: 85.42155
Step #128600, epoch #32150, avg. train loss: 86.15802
Step #128700, epoch #32175, avg. train loss: 86.37321
Step #128800, epoch #32200, avg. train loss: 86.50063
Step #128900, epoch #32225, avg. train loss: 86.58807
Step #129000, epoch #32250, avg. train loss: 87.54261
Step #129100, epoch #32275, avg. train loss: 87.61908
Step #129200, epoch #32300, avg. train loss: 86.95672
Step #129300, epoch #32325, avg. train loss: 86.65925
Step #129400, epoch #32350, avg. train loss: 86.59375
Step #129500, epoch #32375, avg. train loss: 86.95699
Step #129600, epoch #32400, avg. train loss: 86.58485
Step #129700, epoch #32425, avg. train loss: 86.17319
Step #129800, epoch #32450, avg. train loss: 87.03207
Step #129900, epoch #32475, avg. train loss: 87.56243
Step #130000, epoch #32500, avg. train loss: 87.34751
Step #130100, epoch #32525, avg. train loss: 85.36961
Step #130200, epoch #32550, avg. train loss: 86.16549
Step #130300, epoch #32575, avg. train loss: 86.95683
Step #130400, epoch #32600, avg. train loss: 86.73543
Step #130500, epoch #32625, avg. train loss: 87.04708
Step #130600, epoch #32650, avg. train loss: 86.85149
Step #130700, epoch #32675, avg. train loss: 86.45038
Step #130800, epoch #32700, avg. train loss: 86.76584
Step #130900, epoch #32725, avg. train loss: 86.37349
Step #131000, epoch #32750, avg. train loss: 87.06863
Step #131100, epoch #32775, avg. train loss: 85.50732
Step #131200, epoch #32800, avg. train loss: 86.51431
Step #131300, epoch #32825, avg. train loss: 86.16534
Step #131400, epoch #32850, avg. train loss: 86.35818
Step #131500, epoch #32875, avg. train loss: 86.75632
Step #131600, epoch #32900, avg. train loss: 85.71751
Step #131700, epoch #32925, avg. train loss: 86.79356
Step #131800, epoch #32950, avg. train loss: 86.27817
Step #131900, epoch #32975, avg. train loss: 86.22485
Step #132000, epoch #33000, avg. train loss: 85.96484
Step #132100, epoch #33025, avg. train loss: 86.45615
Step #132200, epoch #33050, avg. train loss: 86.86080
Step #132300, epoch #33075, avg. train loss: 86.37291
Step #132400, epoch #33100, avg. train loss: 85.85780
Step #132500, epoch #33125, avg. train loss: 86.81525
Step #132600, epoch #33150, avg. train loss: 86.44047
Step #132700, epoch #33175, avg. train loss: 86.22070
Step #132800, epoch #33200, avg. train loss: 87.24058
Step #132900, epoch #33225, avg. train loss: 85.62637
Step #133000, epoch #33250, avg. train loss: 86.62749
Step #133100, epoch #33275, avg. train loss: 86.50878
Step #133200, epoch #33300, avg. train loss: 87.42300
Step #133300, epoch #33325, avg. train loss: 87.21176
Step #133400, epoch #33350, avg. train loss: 86.64432
Step #133500, epoch #33375, avg. train loss: 85.99575
Step #133600, epoch #33400, avg. train loss: 85.90284
Step #133700, epoch #33425, avg. train loss: 86.34912
Step #133800, epoch #33450, avg. train loss: 85.91577
Step #133900, epoch #33475, avg. train loss: 86.15715
Step #134000, epoch #33500, avg. train loss: 85.77009
Step #134100, epoch #33525, avg. train loss: 86.86048
Step #134200, epoch #33550, avg. train loss: 85.52620
Step #134300, epoch #33575, avg. train loss: 86.72047
Step #134400, epoch #33600, avg. train loss: 86.23235
Step #134500, epoch #33625, avg. train loss: 86.73633
Step #134600, epoch #33650, avg. train loss: 86.16700
Step #134700, epoch #33675, avg. train loss: 86.87482
Step #134800, epoch #33700, avg. train loss: 86.48332
Step #134900, epoch #33725, avg. train loss: 85.97166
Step #135000, epoch #33750, avg. train loss: 86.27155
Step #135100, epoch #33775, avg. train loss: 86.82444
Step #135200, epoch #33800, avg. train loss: 87.15668
Step #135300, epoch #33825, avg. train loss: 85.61960
Step #135400, epoch #33850, avg. train loss: 85.79730
Step #135500, epoch #33875, avg. train loss: 86.09194
Step #135600, epoch #33900, avg. train loss: 86.78163
Step #135700, epoch #33925, avg. train loss: 86.96313
Step #135800, epoch #33950, avg. train loss: 86.06159
Step #135900, epoch #33975, avg. train loss: 85.59383
Step #136000, epoch #34000, avg. train loss: 86.59130
Step #136100, epoch #34025, avg. train loss: 85.77158
Step #136200, epoch #34050, avg. train loss: 87.21231
Step #136300, epoch #34075, avg. train loss: 85.94521
Step #136400, epoch #34100, avg. train loss: 85.59592
Step #136500, epoch #34125, avg. train loss: 86.60818
Step #136600, epoch #34150, avg. train loss: 85.65486
Step #136700, epoch #34175, avg. train loss: 85.93311
Step #136800, epoch #34200, avg. train loss: 86.25320
Step #136900, epoch #34225, avg. train loss: 86.19912
Step #137000, epoch #34250, avg. train loss: 86.65894
Step #137100, epoch #34275, avg. train loss: 86.40671
Step #137200, epoch #34300, avg. train loss: 85.90932
Step #137300, epoch #34325, avg. train loss: 86.74847
Step #137400, epoch #34350, avg. train loss: 86.36962
Step #137500, epoch #34375, avg. train loss: 86.05386
Step #137600, epoch #34400, avg. train loss: 86.27550
Step #137700, epoch #34425, avg. train loss: 86.53777
Step #137800, epoch #34450, avg. train loss: 85.34111
Step #137900, epoch #34475, avg. train loss: 85.81470
Step #138000, epoch #34500, avg. train loss: 86.49122
Step #138100, epoch #34525, avg. train loss: 86.08879
Step #138200, epoch #34550, avg. train loss: 86.71101
Step #138300, epoch #34575, avg. train loss: 85.47634
Step #138400, epoch #34600, avg. train loss: 85.89899
Step #138500, epoch #34625, avg. train loss: 85.10788
Step #138600, epoch #34650, avg. train loss: 85.69936
Step #138700, epoch #34675, avg. train loss: 86.24927
Step #138800, epoch #34700, avg. train loss: 86.25450
Step #138900, epoch #34725, avg. train loss: 87.02222
Step #139000, epoch #34750, avg. train loss: 86.15625
Step #139100, epoch #34775, avg. train loss: 86.37946
Step #139200, epoch #34800, avg. train loss: 86.53811
Step #139300, epoch #34825, avg. train loss: 86.44622
Step #139400, epoch #34850, avg. train loss: 85.27426
Step #139500, epoch #34875, avg. train loss: 86.43803
Step #139600, epoch #34900, avg. train loss: 85.98038
Step #139700, epoch #34925, avg. train loss: 85.56454
Step #139800, epoch #34950, avg. train loss: 86.21397
Step #139900, epoch #34975, avg. train loss: 85.80451
Step #140000, epoch #35000, avg. train loss: 85.91745
Step #140100, epoch #35025, avg. train loss: 86.50146
Step #140200, epoch #35050, avg. train loss: 85.55423
Step #140300, epoch #35075, avg. train loss: 85.10309
Step #140400, epoch #35100, avg. train loss: 85.59864
Step #140500, epoch #35125, avg. train loss: 85.99770
Step #140600, epoch #35150, avg. train loss: 85.89717
Step #140700, epoch #35175, avg. train loss: 85.54572
Step #140800, epoch #35200, avg. train loss: 86.73305
Step #140900, epoch #35225, avg. train loss: 86.78659
Step #141000, epoch #35250, avg. train loss: 86.18167
Step #141100, epoch #35275, avg. train loss: 86.02266
Step #141200, epoch #35300, avg. train loss: 86.39217
Step #141300, epoch #35325, avg. train loss: 85.69143
Step #141400, epoch #35350, avg. train loss: 86.91776
Step #141500, epoch #35375, avg. train loss: 86.54125
Step #141600, epoch #35400, avg. train loss: 85.86526
Step #141700, epoch #35425, avg. train loss: 85.95075
Step #141800, epoch #35450, avg. train loss: 85.14889
Step #141900, epoch #35475, avg. train loss: 86.03248
Step #142000, epoch #35500, avg. train loss: 86.53742
Step #142100, epoch #35525, avg. train loss: 84.44490
Step #142200, epoch #35550, avg. train loss: 85.25695
Step #142300, epoch #35575, avg. train loss: 85.98296
Step #142400, epoch #35600, avg. train loss: 86.15025
Step #142500, epoch #35625, avg. train loss: 85.80692
Step #142600, epoch #35650, avg. train loss: 86.29905
Step #142700, epoch #35675, avg. train loss: 85.48350
Step #142800, epoch #35700, avg. train loss: 85.47845
Step #142900, epoch #35725, avg. train loss: 85.79617
Step #143000, epoch #35750, avg. train loss: 85.35938
Step #143100, epoch #35775, avg. train loss: 85.28541
Step #143200, epoch #35800, avg. train loss: 86.02167
Step #143300, epoch #35825, avg. train loss: 85.75848
Step #143400, epoch #35850, avg. train loss: 85.44476
Step #143500, epoch #35875, avg. train loss: 85.26807
Step #143600, epoch #35900, avg. train loss: 86.50751
Step #143700, epoch #35925, avg. train loss: 85.30490
Step #143800, epoch #35950, avg. train loss: 84.98019
Step #143900, epoch #35975, avg. train loss: 85.98758
Step #144000, epoch #36000, avg. train loss: 85.45869
Step #144100, epoch #36025, avg. train loss: 86.25100
Step #144200, epoch #36050, avg. train loss: 86.66997
Step #144300, epoch #36075, avg. train loss: 85.50954
Step #144400, epoch #36100, avg. train loss: 85.17432
Step #144500, epoch #36125, avg. train loss: 85.15723
Step #144600, epoch #36150, avg. train loss: 85.74139
Step #144700, epoch #36175, avg. train loss: 86.51901
Step #144800, epoch #36200, avg. train loss: 85.17592
Step #144900, epoch #36225, avg. train loss: 85.85918
Step #145000, epoch #36250, avg. train loss: 85.94810
Step #145100, epoch #36275, avg. train loss: 86.25878
Step #145200, epoch #36300, avg. train loss: 85.60750
Step #145300, epoch #36325, avg. train loss: 86.02267
Step #145400, epoch #36350, avg. train loss: 86.15884
Step #145500, epoch #36375, avg. train loss: 85.86211
Step #145600, epoch #36400, avg. train loss: 85.76635
Step #145700, epoch #36425, avg. train loss: 86.76684
Step #145800, epoch #36450, avg. train loss: 85.63221
Step #145900, epoch #36475, avg. train loss: 86.16099
Step #146000, epoch #36500, avg. train loss: 85.88530
Step #146100, epoch #36525, avg. train loss: 85.26977
Step #146200, epoch #36550, avg. train loss: 85.28374
Step #146300, epoch #36575, avg. train loss: 86.17836
Step #146400, epoch #36600, avg. train loss: 85.30623
Step #146500, epoch #36625, avg. train loss: 86.20495
Step #146600, epoch #36650, avg. train loss: 84.92035
Step #146700, epoch #36675, avg. train loss: 85.00406
Step #146800, epoch #36700, avg. train loss: 85.33353
Step #146900, epoch #36725, avg. train loss: 86.48827
Step #147000, epoch #36750, avg. train loss: 86.37196
Step #147100, epoch #36775, avg. train loss: 85.55460
Step #147200, epoch #36800, avg. train loss: 85.48235
Step #147300, epoch #36825, avg. train loss: 85.00209
Step #147400, epoch #36850, avg. train loss: 85.68676
Step #147500, epoch #36875, avg. train loss: 84.97782
Step #147600, epoch #36900, avg. train loss: 85.26958
Step #147700, epoch #36925, avg. train loss: 85.44408
Step #147800, epoch #36950, avg. train loss: 84.89206
Step #147900, epoch #36975, avg. train loss: 85.26973
Step #148000, epoch #37000, avg. train loss: 85.52866
Step #148100, epoch #37025, avg. train loss: 85.62933
Step #148200, epoch #37050, avg. train loss: 85.11014
Step #148300, epoch #37075, avg. train loss: 86.07677
Step #148400, epoch #37100, avg. train loss: 85.62288
Step #148500, epoch #37125, avg. train loss: 85.09532
Step #148600, epoch #37150, avg. train loss: 86.32903
Step #148700, epoch #37175, avg. train loss: 85.71404
Step #148800, epoch #37200, avg. train loss: 86.08549
Step #148900, epoch #37225, avg. train loss: 85.15961
Step #149000, epoch #37250, avg. train loss: 85.03728
Step #149100, epoch #37275, avg. train loss: 86.21502
Step #149200, epoch #37300, avg. train loss: 85.46468
Step #149300, epoch #37325, avg. train loss: 85.88474
Step #149400, epoch #37350, avg. train loss: 86.02109
Step #149500, epoch #37375, avg. train loss: 85.05435
Step #149600, epoch #37400, avg. train loss: 86.86687
Step #149700, epoch #37425, avg. train loss: 85.18554
Step #149800, epoch #37450, avg. train loss: 85.82585
Step #149900, epoch #37475, avg. train loss: 85.43855
Step #150000, epoch #37500, avg. train loss: 85.88586
Step #150100, epoch #37525, avg. train loss: 85.95716
Step #150200, epoch #37550, avg. train loss: 85.78616
Step #150300, epoch #37575, avg. train loss: 85.12395
Step #150400, epoch #37600, avg. train loss: 86.03223
Step #150500, epoch #37625, avg. train loss: 85.15129
Step #150600, epoch #37650, avg. train loss: 86.12930
Step #150700, epoch #37675, avg. train loss: 85.93890
Step #150800, epoch #37700, avg. train loss: 85.08872
Step #150900, epoch #37725, avg. train loss: 85.55681
Step #151000, epoch #37750, avg. train loss: 86.09567
Step #151100, epoch #37775, avg. train loss: 85.75513
Step #151200, epoch #37800, avg. train loss: 85.77853
Step #151300, epoch #37825, avg. train loss: 85.26789
Step #151400, epoch #37850, avg. train loss: 84.60214
Step #151500, epoch #37875, avg. train loss: 85.29268
Step #151600, epoch #37900, avg. train loss: 84.99277
Step #151700, epoch #37925, avg. train loss: 85.63113
Step #151800, epoch #37950, avg. train loss: 84.99895
Step #151900, epoch #37975, avg. train loss: 85.80593
Step #152000, epoch #38000, avg. train loss: 85.16766
Step #152100, epoch #38025, avg. train loss: 85.52428
Step #152200, epoch #38050, avg. train loss: 84.86599
Step #152300, epoch #38075, avg. train loss: 85.22177
Step #152400, epoch #38100, avg. train loss: 85.04764
Step #152500, epoch #38125, avg. train loss: 84.96342
Step #152600, epoch #38150, avg. train loss: 84.75116
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Step #154600, epoch #38650, avg. train loss: 84.94431
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Step #155400, epoch #38850, avg. train loss: 84.99358
Step #155500, epoch #38875, avg. train loss: 84.80859
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Step #156800, epoch #39200, avg. train loss: 85.00768
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Step #157000, epoch #39250, avg. train loss: 85.56413
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Step #157300, epoch #39325, avg. train loss: 84.94560
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Step #158500, epoch #39625, avg. train loss: 85.82393
Step #158600, epoch #39650, avg. train loss: 85.39073
Step #158700, epoch #39675, avg. train loss: 85.11684
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Step #159400, epoch #39850, avg. train loss: 84.44396
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Step #159800, epoch #39950, avg. train loss: 85.97528
Step #159900, epoch #39975, avg. train loss: 84.67873
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Step #160300, epoch #40075, avg. train loss: 84.85595
Step #160400, epoch #40100, avg. train loss: 84.47028
Step #160500, epoch #40125, avg. train loss: 84.43684
Step #160600, epoch #40150, avg. train loss: 85.04984
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Step #160800, epoch #40200, avg. train loss: 85.50070
Step #160900, epoch #40225, avg. train loss: 84.72855
Step #161000, epoch #40250, avg. train loss: 84.76244
Step #161100, epoch #40275, avg. train loss: 85.20898
Step #161200, epoch #40300, avg. train loss: 85.29050
Step #161300, epoch #40325, avg. train loss: 85.57002
Step #161400, epoch #40350, avg. train loss: 85.55780
Step #161500, epoch #40375, avg. train loss: 85.37562
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Step #161700, epoch #40425, avg. train loss: 85.12984
Step #161800, epoch #40450, avg. train loss: 84.32455
Step #161900, epoch #40475, avg. train loss: 83.77597
Step #162000, epoch #40500, avg. train loss: 84.39710
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Step #162200, epoch #40550, avg. train loss: 84.78667
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Step #162600, epoch #40650, avg. train loss: 85.22635
Step #162700, epoch #40675, avg. train loss: 85.36792
Step #162800, epoch #40700, avg. train loss: 85.05005
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Step #163200, epoch #40800, avg. train loss: 84.79635
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Step #163400, epoch #40850, avg. train loss: 84.52883
Step #163500, epoch #40875, avg. train loss: 85.24049
Step #163600, epoch #40900, avg. train loss: 85.61177
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Step #163800, epoch #40950, avg. train loss: 84.46819
Step #163900, epoch #40975, avg. train loss: 85.32798
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Step #164100, epoch #41025, avg. train loss: 84.50229
Step #164200, epoch #41050, avg. train loss: 85.17766
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Step #164900, epoch #41225, avg. train loss: 84.41129
Step #165000, epoch #41250, avg. train loss: 84.53689
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Step #165200, epoch #41300, avg. train loss: 84.10740
Step #165300, epoch #41325, avg. train loss: 84.30913
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Step #165500, epoch #41375, avg. train loss: 85.04612
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Step #166100, epoch #41525, avg. train loss: 84.67777
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Step #168200, epoch #42050, avg. train loss: 85.06702
Step #168300, epoch #42075, avg. train loss: 84.41018
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Step #168600, epoch #42150, avg. train loss: 85.42362
Step #168700, epoch #42175, avg. train loss: 84.60523
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Step #169200, epoch #42300, avg. train loss: 86.42752
Step #169300, epoch #42325, avg. train loss: 85.27340
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Step #170100, epoch #42525, avg. train loss: 84.27364
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Step #170300, epoch #42575, avg. train loss: 84.78502
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Step #171200, epoch #42800, avg. train loss: 84.50710
Step #171300, epoch #42825, avg. train loss: 84.50371
Step #171400, epoch #42850, avg. train loss: 83.67247
Step #171500, epoch #42875, avg. train loss: 83.54203
Step #171600, epoch #42900, avg. train loss: 84.75108
Step #171700, epoch #42925, avg. train loss: 84.66739
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Step #171900, epoch #42975, avg. train loss: 84.50653
Step #172000, epoch #43000, avg. train loss: 84.38560
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Step #172300, epoch #43075, avg. train loss: 85.62103
Step #172400, epoch #43100, avg. train loss: 84.53292
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Step #172600, epoch #43150, avg. train loss: 84.71658
Step #172700, epoch #43175, avg. train loss: 84.69733
Step #172800, epoch #43200, avg. train loss: 84.01876
Step #172900, epoch #43225, avg. train loss: 84.79533
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Step #173200, epoch #43300, avg. train loss: 84.67690
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Step #173400, epoch #43350, avg. train loss: 84.60786
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Step #177200, epoch #44300, avg. train loss: 84.80486
Step #177300, epoch #44325, avg. train loss: 84.09165
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Step #180700, epoch #45175, avg. train loss: 84.83539
Step #180800, epoch #45200, avg. train loss: 84.66919
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Step #181200, epoch #45300, avg. train loss: 83.86841
Step #181300, epoch #45325, avg. train loss: 84.78293
Step #181400, epoch #45350, avg. train loss: 85.46963
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Step #183200, epoch #45800, avg. train loss: 83.53453
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Step #184600, epoch #46150, avg. train loss: 84.58527
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Step #184800, epoch #46200, avg. train loss: 84.82535
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Step #185100, epoch #46275, avg. train loss: 83.49797
Step #185200, epoch #46300, avg. train loss: 84.21928
Step #185300, epoch #46325, avg. train loss: 84.61763
Step #185400, epoch #46350, avg. train loss: 84.30067
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Step #185700, epoch #46425, avg. train loss: 83.64747
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Step #186100, epoch #46525, avg. train loss: 83.59521
Step #186200, epoch #46550, avg. train loss: 83.95302
Step #186300, epoch #46575, avg. train loss: 83.34286
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Step #187100, epoch #46775, avg. train loss: 83.80037
Step #187200, epoch #46800, avg. train loss: 85.49428
Step #187300, epoch #46825, avg. train loss: 83.51218
Step #187400, epoch #46850, avg. train loss: 83.69656
Step #187500, epoch #46875, avg. train loss: 83.73839
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Step #187800, epoch #46950, avg. train loss: 83.35809
Step #187900, epoch #46975, avg. train loss: 84.59022
Step #188000, epoch #47000, avg. train loss: 83.92554
Step #188100, epoch #47025, avg. train loss: 83.79681
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Step #189200, epoch #47300, avg. train loss: 84.26077
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Step #189500, epoch #47375, avg. train loss: 84.43713
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Step #190500, epoch #47625, avg. train loss: 84.37434
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Step #190900, epoch #47725, avg. train loss: 83.15834
Step #191000, epoch #47750, avg. train loss: 83.11613
Step #191100, epoch #47775, avg. train loss: 83.73550
Step #191200, epoch #47800, avg. train loss: 83.65619
Step #191300, epoch #47825, avg. train loss: 84.18398
Step #191400, epoch #47850, avg. train loss: 83.69213
Step #191500, epoch #47875, avg. train loss: 83.56477
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Step #191800, epoch #47950, avg. train loss: 83.82167
Step #191900, epoch #47975, avg. train loss: 84.28369
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Step #192300, epoch #48075, avg. train loss: 83.98273
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Step #192600, epoch #48150, avg. train loss: 83.51333
Step #192700, epoch #48175, avg. train loss: 84.55100
Step #192800, epoch #48200, avg. train loss: 83.67825
Step #192900, epoch #48225, avg. train loss: 83.45531
Step #193000, epoch #48250, avg. train loss: 83.89778
Step #193100, epoch #48275, avg. train loss: 83.00262
Step #193200, epoch #48300, avg. train loss: 84.57935
Step #193300, epoch #48325, avg. train loss: 84.37416
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Step #193600, epoch #48400, avg. train loss: 83.46024
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Step #193800, epoch #48450, avg. train loss: 84.07050
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Step #194200, epoch #48550, avg. train loss: 84.06046
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Step #194400, epoch #48600, avg. train loss: 83.69974
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Step #195400, epoch #48850, avg. train loss: 83.25816
Step #195500, epoch #48875, avg. train loss: 83.89565
Step #195600, epoch #48900, avg. train loss: 84.16424
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Step #195800, epoch #48950, avg. train loss: 84.52521
Step #195900, epoch #48975, avg. train loss: 82.69733
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Step #196100, epoch #49025, avg. train loss: 84.11454
Step #196200, epoch #49050, avg. train loss: 82.91567
Step #196300, epoch #49075, avg. train loss: 83.55486
Step #196400, epoch #49100, avg. train loss: 83.12713
Step #196500, epoch #49125, avg. train loss: 83.75365
Step #196600, epoch #49150, avg. train loss: 83.65366
Step #196700, epoch #49175, avg. train loss: 83.39332
Step #196800, epoch #49200, avg. train loss: 83.46323
Step #196900, epoch #49225, avg. train loss: 83.25723
Step #197000, epoch #49250, avg. train loss: 83.45193
Step #197100, epoch #49275, avg. train loss: 83.95350
Step #197200, epoch #49300, avg. train loss: 82.66438
Step #197300, epoch #49325, avg. train loss: 83.51900
Step #197400, epoch #49350, avg. train loss: 83.48016
Step #197500, epoch #49375, avg. train loss: 83.54552
Step #197600, epoch #49400, avg. train loss: 83.95757
Step #197700, epoch #49425, avg. train loss: 83.33734
Step #197800, epoch #49450, avg. train loss: 84.64153
Step #197900, epoch #49475, avg. train loss: 83.48041
Step #198000, epoch #49500, avg. train loss: 83.86433
Step #198100, epoch #49525, avg. train loss: 82.65139
Step #198200, epoch #49550, avg. train loss: 83.68247
Step #198300, epoch #49575, avg. train loss: 83.06673
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Step #199000, epoch #49750, avg. train loss: 83.28947
Step #199100, epoch #49775, avg. train loss: 82.45369
Step #199200, epoch #49800, avg. train loss: 84.28157
Step #199300, epoch #49825, avg. train loss: 83.25213
Step #199400, epoch #49850, avg. train loss: 83.46122
Step #199500, epoch #49875, avg. train loss: 84.65532
Step #199600, epoch #49900, avg. train loss: 83.67792
Step #199700, epoch #49925, avg. train loss: 83.93346
Step #199800, epoch #49950, avg. train loss: 83.65295
Step #199900, epoch #49975, avg. train loss: 82.89584
Step #200000, epoch #50000, avg. train loss: 84.30370
Step #200100, epoch #50025, avg. train loss: 84.39621
Step #200200, epoch #50050, avg. train loss: 83.12673
Step #200300, epoch #50075, avg. train loss: 83.51953
Step #200400, epoch #50100, avg. train loss: 83.62202
Step #200500, epoch #50125, avg. train loss: 83.50505
Step #200600, epoch #50150, avg. train loss: 84.54917
Step #200700, epoch #50175, avg. train loss: 82.65601
Step #200800, epoch #50200, avg. train loss: 82.94039
Step #200900, epoch #50225, avg. train loss: 83.85288
Step #201000, epoch #50250, avg. train loss: 83.82516
Step #201100, epoch #50275, avg. train loss: 84.20071
Step #201200, epoch #50300, avg. train loss: 83.46467
Step #201300, epoch #50325, avg. train loss: 83.55633
Step #201400, epoch #50350, avg. train loss: 84.02560
Step #201500, epoch #50375, avg. train loss: 83.93992
Step #201600, epoch #50400, avg. train loss: 83.08730
Step #201700, epoch #50425, avg. train loss: 83.69845
Step #201800, epoch #50450, avg. train loss: 83.36790
Step #201900, epoch #50475, avg. train loss: 82.75611
Step #202000, epoch #50500, avg. train loss: 82.84267
Step #202100, epoch #50525, avg. train loss: 83.42888
Step #202200, epoch #50550, avg. train loss: 83.84661
Step #202300, epoch #50575, avg. train loss: 83.67975
Step #202400, epoch #50600, avg. train loss: 83.70647
Step #202500, epoch #50625, avg. train loss: 83.83099
Step #202600, epoch #50650, avg. train loss: 83.61948
Step #202700, epoch #50675, avg. train loss: 84.31162
Step #202800, epoch #50700, avg. train loss: 83.46903
Step #202900, epoch #50725, avg. train loss: 83.08076
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Step #203100, epoch #50775, avg. train loss: 82.80008
Step #203200, epoch #50800, avg. train loss: 84.41888
Step #203300, epoch #50825, avg. train loss: 84.06474
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Step #204100, epoch #51025, avg. train loss: 83.14107
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Step #204300, epoch #51075, avg. train loss: 82.73616
Step #204400, epoch #51100, avg. train loss: 82.70323
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Step #204800, epoch #51200, avg. train loss: 83.39362
Step #204900, epoch #51225, avg. train loss: 82.75182
Step #205000, epoch #51250, avg. train loss: 84.01578
Step #205100, epoch #51275, avg. train loss: 83.37950
Step #205200, epoch #51300, avg. train loss: 83.24487
Step #205300, epoch #51325, avg. train loss: 83.16549
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Step #205500, epoch #51375, avg. train loss: 82.79330
Step #205600, epoch #51400, avg. train loss: 83.49110
Step #205700, epoch #51425, avg. train loss: 82.90900
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Step #206200, epoch #51550, avg. train loss: 83.60417
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Step #207200, epoch #51800, avg. train loss: 83.25173
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Step #208300, epoch #52075, avg. train loss: 83.22977
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Step #208600, epoch #52150, avg. train loss: 83.23405
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Step #210300, epoch #52575, avg. train loss: 83.02708
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Step #210500, epoch #52625, avg. train loss: 83.33804
Step #210600, epoch #52650, avg. train loss: 83.35815
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Step #211100, epoch #52775, avg. train loss: 83.26124
Step #211200, epoch #52800, avg. train loss: 83.74609
Step #211300, epoch #52825, avg. train loss: 83.33996
Step #211400, epoch #52850, avg. train loss: 84.22080
Step #211500, epoch #52875, avg. train loss: 83.26318
Step #211600, epoch #52900, avg. train loss: 83.38206
Step #211700, epoch #52925, avg. train loss: 82.69524
Step #211800, epoch #52950, avg. train loss: 82.80871
Step #211900, epoch #52975, avg. train loss: 83.42185
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Step #212200, epoch #53050, avg. train loss: 82.85456
Step #212300, epoch #53075, avg. train loss: 82.87536
Step #212400, epoch #53100, avg. train loss: 83.69897
Step #212500, epoch #53125, avg. train loss: 83.67041
Step #212600, epoch #53150, avg. train loss: 82.82459
Step #212700, epoch #53175, avg. train loss: 83.07402
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Step #212900, epoch #53225, avg. train loss: 83.07193
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Step #213300, epoch #53325, avg. train loss: 83.17426
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Step #213500, epoch #53375, avg. train loss: 82.96355
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Step #214600, epoch #53650, avg. train loss: 83.68027
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Step #215100, epoch #53775, avg. train loss: 83.98817
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Step #215300, epoch #53825, avg. train loss: 83.60133
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Step #216200, epoch #54050, avg. train loss: 82.90339
Step #216300, epoch #54075, avg. train loss: 83.11170
Step #216400, epoch #54100, avg. train loss: 82.48184
Step #216500, epoch #54125, avg. train loss: 83.38316
Step #216600, epoch #54150, avg. train loss: 82.83825
Step #216700, epoch #54175, avg. train loss: 83.62802
Step #216800, epoch #54200, avg. train loss: 83.76862
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Step #217000, epoch #54250, avg. train loss: 83.77566
Step #217100, epoch #54275, avg. train loss: 83.41082
Step #217200, epoch #54300, avg. train loss: 83.04613
Step #217300, epoch #54325, avg. train loss: 82.90741
Step #217400, epoch #54350, avg. train loss: 83.92815
Step #217500, epoch #54375, avg. train loss: 82.62285
Step #217600, epoch #54400, avg. train loss: 83.16617
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Step #218100, epoch #54525, avg. train loss: 83.94751
Step #218200, epoch #54550, avg. train loss: 83.59027
Step #218300, epoch #54575, avg. train loss: 81.98648
Step #218400, epoch #54600, avg. train loss: 83.32941
Step #218500, epoch #54625, avg. train loss: 83.44845
Step #218600, epoch #54650, avg. train loss: 83.32973
Step #218700, epoch #54675, avg. train loss: 82.72543
Step #218800, epoch #54700, avg. train loss: 83.50576
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Step #219200, epoch #54800, avg. train loss: 83.47684
Step #219300, epoch #54825, avg. train loss: 82.59058
Step #219400, epoch #54850, avg. train loss: 82.29830
Step #219500, epoch #54875, avg. train loss: 83.12559
Step #219600, epoch #54900, avg. train loss: 82.44389
Step #219700, epoch #54925, avg. train loss: 83.07150
Step #219800, epoch #54950, avg. train loss: 83.63245
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Step #220200, epoch #55050, avg. train loss: 83.28736
Step #220300, epoch #55075, avg. train loss: 82.76279
Step #220400, epoch #55100, avg. train loss: 83.10152
Step #220500, epoch #55125, avg. train loss: 82.49473
Step #220600, epoch #55150, avg. train loss: 83.04893
Step #220700, epoch #55175, avg. train loss: 83.19807
Step #220800, epoch #55200, avg. train loss: 83.41148
Step #220900, epoch #55225, avg. train loss: 83.23347
Step #221000, epoch #55250, avg. train loss: 81.91672
Step #221100, epoch #55275, avg. train loss: 82.83294
Step #221200, epoch #55300, avg. train loss: 82.17080
Step #221300, epoch #55325, avg. train loss: 82.49314
Step #221400, epoch #55350, avg. train loss: 82.80588
Step #221500, epoch #55375, avg. train loss: 82.57908
Step #221600, epoch #55400, avg. train loss: 82.69957
Step #221700, epoch #55425, avg. train loss: 82.09683
Step #221800, epoch #55450, avg. train loss: 82.12766
Step #221900, epoch #55475, avg. train loss: 82.39939
Step #222000, epoch #55500, avg. train loss: 82.74677
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Step #222400, epoch #55600, avg. train loss: 83.40968
Step #222500, epoch #55625, avg. train loss: 82.79317
Step #222600, epoch #55650, avg. train loss: 83.92461
Step #222700, epoch #55675, avg. train loss: 83.30598
Step #222800, epoch #55700, avg. train loss: 84.68182
Step #222900, epoch #55725, avg. train loss: 83.34616
Step #223000, epoch #55750, avg. train loss: 82.49612
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Step #223200, epoch #55800, avg. train loss: 82.96523
Step #223300, epoch #55825, avg. train loss: 82.97618
Step #223400, epoch #55850, avg. train loss: 83.19072
Step #223500, epoch #55875, avg. train loss: 83.58192
Step #223600, epoch #55900, avg. train loss: 82.86729
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Step #224000, epoch #56000, avg. train loss: 82.47546
Step #224100, epoch #56025, avg. train loss: 82.35754
Step #224200, epoch #56050, avg. train loss: 82.46928
Step #224300, epoch #56075, avg. train loss: 83.04184
Step #224400, epoch #56100, avg. train loss: 81.99298
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Step #228700, epoch #57175, avg. train loss: 83.67738
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Step #229200, epoch #57300, avg. train loss: 82.82951
Step #229300, epoch #57325, avg. train loss: 82.67564
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Step #231800, epoch #57950, avg. train loss: 82.05560
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Step #232400, epoch #58100, avg. train loss: 83.00100
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Step #232600, epoch #58150, avg. train loss: 82.34195
Step #232700, epoch #58175, avg. train loss: 82.60711
Step #232800, epoch #58200, avg. train loss: 83.16794
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Step #233300, epoch #58325, avg. train loss: 82.62629
Step #233400, epoch #58350, avg. train loss: 83.08929
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Step #233700, epoch #58425, avg. train loss: 82.52428
Step #233800, epoch #58450, avg. train loss: 82.33102
Step #233900, epoch #58475, avg. train loss: 82.10862
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Step #237100, epoch #59275, avg. train loss: 82.94333
Step #237200, epoch #59300, avg. train loss: 82.91723
Step #237300, epoch #59325, avg. train loss: 82.57114
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Step #241300, epoch #60325, avg. train loss: 82.76099
Step #241400, epoch #60350, avg. train loss: 83.00458
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Step #260300, epoch #65075, avg. train loss: 81.94065
Step #260400, epoch #65100, avg. train loss: 82.08088
Step #260500, epoch #65125, avg. train loss: 81.20811
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Step #261500, epoch #65375, avg. train loss: 83.14457
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Step #262000, epoch #65500, avg. train loss: 82.16838
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Step #262300, epoch #65575, avg. train loss: 82.56624
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Step #263200, epoch #65800, avg. train loss: 82.32770
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Step #263400, epoch #65850, avg. train loss: 82.80196
Step #263500, epoch #65875, avg. train loss: 82.23715
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Step #263800, epoch #65950, avg. train loss: 82.07204
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Step #264200, epoch #66050, avg. train loss: 81.58903
Step #264300, epoch #66075, avg. train loss: 81.31133
Step #264400, epoch #66100, avg. train loss: 81.73965
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Step #264700, epoch #66175, avg. train loss: 82.31216
Step #264800, epoch #66200, avg. train loss: 81.53168
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Step #265200, epoch #66300, avg. train loss: 81.64083
Step #265300, epoch #66325, avg. train loss: 82.07944
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Step #265500, epoch #66375, avg. train loss: 81.90569
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Step #265800, epoch #66450, avg. train loss: 82.23382
Step #265900, epoch #66475, avg. train loss: 82.25253
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Step #266300, epoch #66575, avg. train loss: 83.14600
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Step #267900, epoch #66975, avg. train loss: 83.22879
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Step #269100, epoch #67275, avg. train loss: 82.64599
Step #269200, epoch #67300, avg. train loss: 82.55855
Step #269300, epoch #67325, avg. train loss: 82.37029
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Step #269800, epoch #67450, avg. train loss: 82.17104
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Step #270200, epoch #67550, avg. train loss: 82.04314
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Step #270600, epoch #67650, avg. train loss: 81.38804
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Step #271400, epoch #67850, avg. train loss: 81.49636
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Step #272900, epoch #68225, avg. train loss: 81.03596
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Step #273200, epoch #68300, avg. train loss: 81.49068
Step #273300, epoch #68325, avg. train loss: 81.68196
Step #273400, epoch #68350, avg. train loss: 81.21694
Step #273500, epoch #68375, avg. train loss: 81.59406
Step #273600, epoch #68400, avg. train loss: 81.82175
Step #273700, epoch #68425, avg. train loss: 81.79678
Step #273800, epoch #68450, avg. train loss: 82.15856
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Step #277200, epoch #69300, avg. train loss: 81.82265
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Step #278300, epoch #69575, avg. train loss: 81.68542
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Step #281000, epoch #70250, avg. train loss: 81.37533
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Step #281300, epoch #70325, avg. train loss: 81.60512
Step #281400, epoch #70350, avg. train loss: 81.63720
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Step #291600, epoch #72900, avg. train loss: 81.99302
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Step #292600, epoch #73150, avg. train loss: 80.80997
Step #292700, epoch #73175, avg. train loss: 81.21153
Step #292800, epoch #73200, avg. train loss: 81.65306
Step #292900, epoch #73225, avg. train loss: 81.50278
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Step #293100, epoch #73275, avg. train loss: 82.02841
Step #293200, epoch #73300, avg. train loss: 81.40379
Step #293300, epoch #73325, avg. train loss: 82.24272
Step #293400, epoch #73350, avg. train loss: 81.28915
Step #293500, epoch #73375, avg. train loss: 80.22737
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Step #293700, epoch #73425, avg. train loss: 81.20222
Step #293800, epoch #73450, avg. train loss: 80.90606
Step #293900, epoch #73475, avg. train loss: 81.34643
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Step #294200, epoch #73550, avg. train loss: 80.65664
Step #294300, epoch #73575, avg. train loss: 81.48456
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Step #294500, epoch #73625, avg. train loss: 81.31096
Step #294600, epoch #73650, avg. train loss: 81.56212
Step #294700, epoch #73675, avg. train loss: 81.35194
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Step #295200, epoch #73800, avg. train loss: 81.79528
Step #295300, epoch #73825, avg. train loss: 81.16335
Step #295400, epoch #73850, avg. train loss: 80.74354
Step #295500, epoch #73875, avg. train loss: 80.64295
Step #295600, epoch #73900, avg. train loss: 81.88613
Step #295700, epoch #73925, avg. train loss: 82.37402
Step #295800, epoch #73950, avg. train loss: 80.74409
Step #295900, epoch #73975, avg. train loss: 81.30775
Step #296000, epoch #74000, avg. train loss: 81.56546
Step #296100, epoch #74025, avg. train loss: 81.81644
Step #296200, epoch #74050, avg. train loss: 81.40825
Step #296300, epoch #74075, avg. train loss: 81.57802
Step #296400, epoch #74100, avg. train loss: 82.56271
Step #296500, epoch #74125, avg. train loss: 81.06610
Step #296600, epoch #74150, avg. train loss: 80.87451
Step #296700, epoch #74175, avg. train loss: 81.45281
Step #296800, epoch #74200, avg. train loss: 81.14645
Step #296900, epoch #74225, avg. train loss: 80.86128
Step #297000, epoch #74250, avg. train loss: 81.09090
Step #297100, epoch #74275, avg. train loss: 80.53520
Step #297200, epoch #74300, avg. train loss: 82.57864
Step #297300, epoch #74325, avg. train loss: 81.52689
Step #297400, epoch #74350, avg. train loss: 81.38336
Step #297500, epoch #74375, avg. train loss: 81.40083
Step #297600, epoch #74400, avg. train loss: 81.31266
Step #297700, epoch #74425, avg. train loss: 81.35596
Step #297800, epoch #74450, avg. train loss: 82.34517
Step #297900, epoch #74475, avg. train loss: 81.38045
Step #298000, epoch #74500, avg. train loss: 81.12930
Step #298100, epoch #74525, avg. train loss: 81.71455
Step #298200, epoch #74550, avg. train loss: 82.79408
Step #298300, epoch #74575, avg. train loss: 81.46931
Step #298400, epoch #74600, avg. train loss: 81.60206
Step #298500, epoch #74625, avg. train loss: 81.59718
Step #298600, epoch #74650, avg. train loss: 81.57714
Step #298700, epoch #74675, avg. train loss: 81.42300
Step #298800, epoch #74700, avg. train loss: 81.41348
Step #298900, epoch #74725, avg. train loss: 81.90736
Step #299000, epoch #74750, avg. train loss: 81.02139
Step #299100, epoch #74775, avg. train loss: 81.17518
Step #299200, epoch #74800, avg. train loss: 81.22745
Step #299300, epoch #74825, avg. train loss: 80.42084
Step #299400, epoch #74850, avg. train loss: 81.59566
Step #299500, epoch #74875, avg. train loss: 81.06145
Step #299600, epoch #74900, avg. train loss: 81.09778
Step #299700, epoch #74925, avg. train loss: 80.85955
Step #299800, epoch #74950, avg. train loss: 81.42062
Step #299900, epoch #74975, avg. train loss: 82.39983
Step #300000, epoch #75000, avg. train loss: 81.06033
Out[ ]:
TensorFlowDNNRegressor(batch_size=32, clip_gradients=5.0, config=None,
continue_training=False, dropout=None,
hidden_units=[85, 40, 20, 10], learning_rate=0.01, n_classes=0,
optimizer='Adagrad', steps=300000, verbose=1)
In [54]:
#Measure accuracy
score = np.sqrt(metrics.mean_squared_error(regressor.predict(x_test), y_test))
print("Final score (RMSE): {}".format(score))
Final score (RMSE): 148.8486328125
In [58]:
#Make predictions
pred = regressor.predict(x_test)
predDF = pd.DataFrame(pred)
dfytest=pd.DataFrame(y_test)
dfytest.reset_index(inplace=True, drop=True)
predDF.reset_index(inplace=True, drop=True)
df2 = pd.concat([predDF, dfytest], axis=1,ignore_index=True)
df2.columns=['Predicted', 'Actual']
df2
Out[58]:
Predicted
Actual
0
254.960403
246.399994
1
231.180801
223.199997
2
229.887314
293.000000
3
183.837448
235.899994
4
195.853485
314.899994
5
309.261749
214.300003
6
516.272095
198.800003
7
229.286972
221.899994
8
170.185654
219.100006
9
234.212799
289.200012
10
309.967682
237.899994
11
445.900421
338.899994
12
219.405411
250.000000
13
172.927505
199.899994
14
209.062073
182.300003
15
194.343246
276.799988
16
202.361160
248.199997
17
278.455994
249.300003
18
214.124252
182.600006
19
118.299248
198.000000
20
321.295166
263.600006
21
179.103043
272.399994
22
253.123367
244.699997
23
226.671173
145.100006
24
652.219055
236.300003
25
193.852951
250.699997
26
834.208740
197.699997
27
157.816330
190.800003
28
366.878021
206.199997
29
194.218948
238.300003
30
228.004303
234.699997
31
195.569427
215.300003
32
264.847412
183.899994
33
203.223770
195.500000
34
445.268951
174.199997
35
198.955872
259.700012
36
226.144150
202.899994
37
421.919556
291.500000
38
193.219376
158.300003
39
205.446655
165.899994
40
250.437561
300.200012
In [ ]:
Content source: jbliss1234/ML
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