In [ ]:
In [48]:
report = "../report/report.txt"
header = " #%{0}s%10s%10s%10s%10s%10s%10s"
fields = "Architecture\tLambda\tDecay\tMomtm\tAct_Fn\tScore\tTime".split("\t")
fmt = "%2d%{0}s%10g%10g%10g%10s%10g%10g"
print(fields)
def print_header(width):
print(header.format(width) % tuple(fields))
def print_table(lines):
max_width = max(map(lambda x: len(x[0]), lines))
max_width += 1
print_header(max_width)
for i,line in enumerate(lines):
print(fmt.format(max_width) % tuple([i+1] + line))
with open(report) as report:
lines = []
clean = lambda x: re.sub(r"(\s+)?[,:|]\s+[a-z]+$", "", x)
for line in report:
line = line.strip()
if not line:
continue
if line.startswith("##"):
if lines:
print_table(lines)
lines = []
print(line)
elif line.startswith("arch"):
line = map(clean, line.split('=')[1:])
for i in [1,2,3,5,6]:
line[i] = float(line[i])
lines.append(line)
else:
print(line)
print_table(lines)
['Architecture', 'Lambda', 'Decay', 'Momtm', 'Act_Fn', 'Score', 'Time']
## (d) Linear Activation
Best Config: architecture = [50, 50, 50, 50, 2], lambda = 0.0, decay = 0.0, momentum = 0.0, actfn = linear, best_acc = 0.841617658418
Mean Time = 7.24027329683seconds, |Models| = 4, Total Time = 28.9610931873seconds
Best Config: architecture = [50, 800, 800, 500, 300, 2], lambda = 0.0, decay = 0.0, momentum = 0.0, actfn = linear, best_acc = 0.847499330564
Mean Time = 47.4305422306seconds, |Models| = 5, Total Time = 237.152711153seconds
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 2] 0 0 0 linear 0.832622 6.32704
2 [50, 50, 2] 0 0 0 linear 0.836159 5.44851
3 [50, 50, 50, 2] 0 0 0 linear 0.839004 7.55398
4 [50, 50, 50, 50, 2] 0 0 0 linear 0.841618 9.63156
5 [50, 50, 2] 0 0 0 linear 0.837581 5.44945
6 [50, 500, 2] 0 0 0 linear 0.840042 22.7603
7 [50, 500, 300, 2] 0 0 0 linear 0.843386 35.7083
8 [50, 800, 500, 300, 2] 0 0 0 linear 0.845231 67.9852
9 [50, 800, 800, 500, 300, 2] 0 0 0 linear 0.847499 105.25
## (e) Sigmoid Activation
Best Config: architecture = [50, 500, 2], lambda = 0.0, decay = 0.0, momentum = 0.0, actfn = sigmoid, best_acc = 0.754891784386
Mean Time = 164.787512875seconds, |Models| = 5, Total Time = 823.937564373seconds
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 50, 2] 0 0 0 sigmoid 0.746588 8.94158
2 [50, 500, 2] 0 0 0 sigmoid 0.754892 76.4045
3 [50, 500, 300, 2] 0 0 0 sigmoid 0.717564 124.218
4 [50, 800, 500, 300, 2] 0 0 0 sigmoid 0.717564 244.296
5 [50, 800, 800, 500, 300, 2] 0 0 0 sigmoid 0.717564 370.078
## (f) ReLu Activation
Best Config: architecture = [50, 50, 2], lambda = 0.0, decay = 0.0, momentum = 0.0, actfn = relu, best_acc = 0.82208895373
Mean Time = 77.6921462059seconds, |Models| = 5, Total Time = 388.46073103seconds
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 50, 2] 0 0 0 relu 0.822089 6.61757
2 [50, 500, 2] 0 0 0 relu 0.818283 36.0388
3 [50, 500, 300, 2] 0 0 0 relu 0.805328 58.1833
4 [50, 800, 500, 300, 2] 0 0 0 relu 0.805597 113.869
5 [50, 800, 800, 500, 300, 2] 0 0 0 relu 0.791835 173.752
## (g) Regularization Coefficients
Best Config: architecture = [50, 800, 500, 300, 2], lambda = 1e-06, decay = 0.0, momentum = 0.0, actfn = relu, best_acc = 0.8067120346
Mean Time = 125.604739046seconds, |Models| = 5, Total Time = 628.02369523seconds
('Best Regularization Coefficient=', 1e-06)
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 800, 500, 300, 2] 1e-07 0 0 relu 0.802868 125.633
2 [50, 800, 500, 300, 2] 5e-07 0 0 relu 0.80479 125.408
3 [50, 800, 500, 300, 2] 1e-06 0 0 relu 0.806712 126.387
4 [50, 800, 500, 300, 2] 5e-06 0 0 relu 0.805213 125.781
5 [50, 800, 500, 300, 2] 1e-05 0 0 relu 0.798793 124.815
## (h) Regularization Coefficients -- Early stop
Epoch 00009: early stopping
Best Config: architecture = [50, 800, 500, 300, 2], lambda = 5e-07, decay = 0.0, momentum = 0.0, actfn = relu, best_acc = 0.80313689471
Mean Time = 101.398305035seconds, |Models| = 5, Total Time = 506.991525173seconds
('Best Regularization Coefficient with early stopping=', 5e-07)
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 800, 500, 300, 2] 1e-07 0 0 relu 0.802868 116.136
2 [50, 800, 500, 300, 2] 5e-07 0 0 relu 0.803137 116.616
3 [50, 800, 500, 300, 2] 1e-06 0 0 relu 0.790835 116.909
4 [50, 800, 500, 300, 2] 5e-06 0 0 relu 0.754507 40.0303
5 [50, 800, 500, 300, 2] 1e-05 0 0 relu 0.797947 117.299
## (i) SGD Decay
Best Config: architecture = [50, 800, 500, 300, 2], lambda = 5e-07, decay = 5e-05, momentum = 0.0, actfn = relu, best_acc = 0.794602700158
Mean Time = 411.436831196seconds, |Models| = 6, Total Time = 2468.62098718seconds
('Best Decay', 5e-05)
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 800, 500, 300, 2] 5e-07 1e-05 0 relu 0.717564 409.972
2 [50, 800, 500, 300, 2] 5e-07 5e-05 0 relu 0.794603 410.182
3 [50, 800, 500, 300, 2] 5e-07 0.0001 0 relu 0.717141 413.814
4 [50, 800, 500, 300, 2] 5e-07 0.0003 0 relu 0.718141 410.25
5 [50, 800, 500, 300, 2] 5e-07 0.0007 0 relu 0.295199 413.014
6 [50, 800, 500, 300, 2] 5e-07 0.001 0 relu 0.778688 411.389
## (j) SGD Momentum
Best Config: architecture = [50, 800, 500, 300, 2], lambda = 0.0, decay = 5e-05, momentum = 0.99, actfn = relu, best_acc = 0.848345062112
Mean Time = 194.935000753seconds, |Models| = 5, Total Time = 974.675003767seconds
('Best moemntum', 0.99)
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 800, 500, 300, 2] 0 5e-05 0.99 relu 0.848345 194.788
2 [50, 800, 500, 300, 2] 0 5e-05 0.98 relu 0.818937 195.591
3 [50, 800, 500, 300, 2] 0 5e-05 0.95 relu 0.785761 195.349
4 [50, 800, 500, 300, 2] 0 5e-05 0.9 relu 0.766655 194.508
5 [50, 800, 500, 300, 2] 0 5e-05 0.85 relu 0.724292 194.438
## (k) Combining all
Epoch 00008: early stopping
Best Config: architecture = [50, 800, 500, 300, 2], lambda = 5e-07, decay = 5e-05, momentum = 0.99, actfn = relu, best_acc = 0.768846344633
Mean Time = 36.4348239899seconds, |Models| = 1, Total Time = 36.4348239899seconds
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 800, 500, 300, 2] 5e-07 5e-05 0.99 relu 0.768846 36.4348
## (j) Grid Search
Epoch 00014: early stopping
Epoch 00009: early stopping
Epoch 00010: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00009: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00009: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00007: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Epoch 00008: early stopping
Best Config: architecture = [50, 800, 800, 500, 300, 2], lambda = 5e-07, decay = 1e-05, momentum = 0.99, actfn = relu, best_acc = 0.875293123297
Mean Time = 187.222276389seconds, |Models| = 75, Total Time = 14041.6707292seconds
# Architecture Lambda Decay Momtm Act_Fn Score Time
1 [50, 50, 2] 1e-07 1e-05 0.99 relu 0.845154 20.4715
2 [50, 50, 2] 1e-07 5e-05 0.99 relu 0.842771 20.3143
3 [50, 50, 2] 1e-07 0.0001 0.99 relu 0.805674 3.80574
4 [50, 50, 2] 5e-07 1e-05 0.99 relu 0.845231 20.3806
5 [50, 50, 2] 5e-07 5e-05 0.99 relu 0.845001 20.5079
6 [50, 50, 2] 5e-07 0.0001 0.99 relu 0.842771 20.161
7 [50, 50, 2] 1e-06 1e-05 0.99 relu 0.850229 20.5862
8 [50, 50, 2] 1e-06 5e-05 0.99 relu 0.844424 20.2211
9 [50, 50, 2] 1e-06 0.0001 0.99 relu 0.847768 20.3865
10 [50, 50, 2] 5e-06 1e-05 0.99 relu 0.847269 20.7574
11 [50, 50, 2] 5e-06 5e-05 0.99 relu 0.841579 20.5422
12 [50, 50, 2] 5e-06 0.0001 0.99 relu 0.836505 20.1935
13 [50, 50, 2] 1e-05 1e-05 0.99 relu 0.844462 20.7328
14 [50, 50, 2] 1e-05 5e-05 0.99 relu 0.844501 20.9433
15 [50, 50, 2] 1e-05 0.0001 0.99 relu 0.842656 20.1146
16 [50, 500, 2] 1e-07 1e-05 0.99 relu 0.851228 111.938
17 [50, 500, 2] 1e-07 5e-05 0.99 relu 0.810402 12.2399
18 [50, 500, 2] 1e-07 0.0001 0.99 relu 0.844693 112.215
19 [50, 500, 2] 5e-07 1e-05 0.99 relu 0.848729 112.914
20 [50, 500, 2] 5e-07 5e-05 0.99 relu 0.847153 112.21
21 [50, 500, 2] 5e-07 0.0001 0.99 relu 0.847192 111.397
22 [50, 500, 2] 1e-06 1e-05 0.99 relu 0.850575 112.272
23 [50, 500, 2] 1e-06 5e-05 0.99 relu 0.807865 13.1088
24 [50, 500, 2] 1e-06 0.0001 0.99 relu 0.843924 112.289
25 [50, 500, 2] 5e-06 1e-05 0.99 relu 0.850921 112.793
26 [50, 500, 2] 5e-06 5e-05 0.99 relu 0.845116 113.816
27 [50, 500, 2] 5e-06 0.0001 0.99 relu 0.843501 113.023
28 [50, 500, 2] 1e-05 1e-05 0.99 relu 0.85019 114.008
29 [50, 500, 2] 1e-05 5e-05 0.99 relu 0.847653 112.867
30 [50, 500, 2] 1e-05 0.0001 0.99 relu 0.844847 112.733
31 [50, 500, 300, 2] 1e-07 1e-05 0.99 relu 0.861608 188.814
32 [50, 500, 300, 2] 1e-07 5e-05 0.99 relu 0.855572 187.028
33 [50, 500, 300, 2] 1e-07 0.0001 0.99 relu 0.790797 18.3032
34 [50, 500, 300, 2] 5e-07 1e-05 0.99 relu 0.861569 188.087
35 [50, 500, 300, 2] 5e-07 5e-05 0.99 relu 0.789951 18.1336
36 [50, 500, 300, 2] 5e-07 0.0001 0.99 relu 0.80602 20.3596
37 [50, 500, 300, 2] 1e-06 1e-05 0.99 relu 0.861954 188.927
38 [50, 500, 300, 2] 1e-06 5e-05 0.99 relu 0.851305 190.002
39 [50, 500, 300, 2] 1e-06 0.0001 0.99 relu 0.851074 189.165
40 [50, 500, 300, 2] 5e-06 1e-05 0.99 relu 0.797447 18.0872
41 [50, 500, 300, 2] 5e-06 5e-05 0.99 relu 0.857533 187.847
42 [50, 500, 300, 2] 5e-06 0.0001 0.99 relu 0.856802 188.897
43 [50, 500, 300, 2] 1e-05 1e-05 0.99 relu 0.858801 188.426
44 [50, 500, 300, 2] 1e-05 5e-05 0.99 relu 0.856572 189.707
45 [50, 500, 300, 2] 1e-05 0.0001 0.99 relu 0.855957 189.398
46 [50, 800, 500, 300, 2] 1e-07 1e-05 0.99 relu 0.773113 36.0215
47 [50, 800, 500, 300, 2] 1e-07 5e-05 0.99 relu 0.86649 384.123
48 [50, 800, 500, 300, 2] 1e-07 0.0001 0.99 relu 0.752547 36.385
49 [50, 800, 500, 300, 2] 5e-07 1e-05 0.99 relu 0.869411 384.686
50 [50, 800, 500, 300, 2] 5e-07 5e-05 0.99 relu 0.862915 382.734
51 [50, 800, 500, 300, 2] 5e-07 0.0001 0.99 relu 0.861492 387.472
52 [50, 800, 500, 300, 2] 1e-06 1e-05 0.99 relu 0.868719 385.912
53 [50, 800, 500, 300, 2] 1e-06 5e-05 0.99 relu 0.86526 385.432
54 [50, 800, 500, 300, 2] 1e-06 0.0001 0.99 relu 0.859801 386.415
55 [50, 800, 500, 300, 2] 5e-06 1e-05 0.99 relu 0.775497 40.4417
56 [50, 800, 500, 300, 2] 5e-06 5e-05 0.99 relu 0.861492 384.428
57 [50, 800, 500, 300, 2] 5e-06 0.0001 0.99 relu 0.863991 384.855
58 [50, 800, 500, 300, 2] 1e-05 1e-05 0.99 relu 0.776381 36.3755
59 [50, 800, 500, 300, 2] 1e-05 5e-05 0.99 relu 0.866682 385.443
60 [50, 800, 500, 300, 2] 1e-05 0.0001 0.99 relu 0.860723 384.931
61 [50, 800, 800, 500, 300, 2] 1e-07 1e-05 0.99 relu 0.754315 56.1611
62 [50, 800, 800, 500, 300, 2] 1e-07 5e-05 0.99 relu 0.867874 602.568
63 [50, 800, 800, 500, 300, 2] 1e-07 0.0001 0.99 relu 0.861877 600.322
64 [50, 800, 800, 500, 300, 2] 5e-07 1e-05 0.99 relu 0.875293 595.138
65 [50, 800, 800, 500, 300, 2] 5e-07 5e-05 0.99 relu 0.870334 600.348
66 [50, 800, 800, 500, 300, 2] 5e-07 0.0001 0.99 relu 0.738746 56.2818
67 [50, 800, 800, 500, 300, 2] 1e-06 1e-05 0.99 relu 0.874371 598.163
68 [50, 800, 800, 500, 300, 2] 1e-06 5e-05 0.99 relu 0.870488 597.95
69 [50, 800, 800, 500, 300, 2] 1e-06 0.0001 0.99 relu 0.861723 601.545
70 [50, 800, 800, 500, 300, 2] 5e-06 1e-05 0.99 relu 0.724561 50.2382
71 [50, 800, 800, 500, 300, 2] 5e-06 5e-05 0.99 relu 0.87487 598.255
72 [50, 800, 800, 500, 300, 2] 5e-06 0.0001 0.99 relu 0.869219 599.841
73 [50, 800, 800, 500, 300, 2] 1e-05 1e-05 0.99 relu 0.734364 56.2232
74 [50, 800, 800, 500, 300, 2] 1e-05 5e-05 0.99 relu 0.734825 55.9429
75 [50, 800, 800, 500, 300, 2] 1e-05 0.0001 0.99 relu 0.741245 55.9157
In [24]:
import re
s = 'architecture=[50, 500, 2], lambda=5e-06, decay=5e-05, momentum=0.99, actfn=relu: score=0.816053507421 | time=11.3747119904'
ss = s.split('=')[1:]
def clean(t):
return
map(clean, ss)
Out[24]:
['[50, 500, 2]',
'5e-06',
'5e-05',
'0.99',
'relu',
'0.816053507421',
'11.3747119904']
In [7]:
Out[7]:
0.0001
In [ ]:
Content source: thammegowda/notes
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