[transfer_0] training getter supervised:
0 train: [0] = 0.412
0 train: [0] = 88.7%
0 val: [0] = 0.2115
0 val: [0] = 94.0%
1 train: [0] = 0.1873
1 train: [0] = 94.4%
1 val: [0] = 0.1682
1 val: [0] = 95.3%
2 train: [0] = 0.1375
2 train: [0] = 95.8%
2 val: [0] = 0.1283
2 val: [0] = 96.2%
3 train: [0] = 0.1076
3 train: [0] = 96.7%
3 val: [0] = 0.1066
3 val: [0] = 97.0%
4 train: [0] = 0.0897
4 train: [0] = 97.3%
4 val: [0] = 0.09546
4 val: [0] = 97.2%
5 train: [0] = 0.07358
5 train: [0] = 97.6%
5 val: [0] = 0.09906
5 val: [0] = 97.1%
6 train: [0] = 0.06397
6 train: [0] = 98.0%
6 val: [0] = 0.1047
6 val: [0] = 96.8%
7 train: [0] = 0.05445
7 train: [0] = 98.3%
7 val: [0] = 0.09433
7 val: [0] = 97.2%
8 train: [0] = 0.04622
8 train: [0] = 98.6%
8 val: [0] = 0.0937
8 val: [0] = 97.4%
9 train: [0] = 0.0411
9 train: [0] = 98.7%
9 val: [0] = 0.09843
9 val: [0] = 97.3%
10 train: [0] = 0.0342
10 train: [0] = 99.0%
10 val: [0] = 0.09711
10 val: [0] = 97.4%
11 train: [0] = 0.03214
11 train: [0] = 99.0%
11 val: [0] = 0.1052
11 val: [0] = 97.2%
12 train: [0] = 0.02694
12 train: [0] = 99.2%
12 val: [0] = 0.09382
12 val: [0] = 97.6%
13 train: [0] = 0.02507
13 train: [0] = 99.2%
13 val: [0] = 0.1093
13 val: [0] = 97.2%
14 train: [0] = 0.02151
14 train: [0] = 99.3%
14 val: [0] = 0.1084
14 val: [0] = 97.4%
15 train: [0] = 0.01758
15 train: [0] = 99.4%
15 val: [0] = 0.1145
15 val: [0] = 97.3%
16 train: [0] = 0.01808
16 train: [0] = 99.4%
16 val: [0] = 0.1156
16 val: [0] = 97.2%
17 train: [0] = 0.01459
17 train: [0] = 99.5%
17 val: [0] = 0.1227
17 val: [0] = 97.2%
18 train: [0] = 0.01504
18 train: [0] = 99.5%
18 val: [0] = 0.116
18 val: [0] = 97.5%
19 train: [0] = 0.01221
19 train: [0] = 99.6%
19 val: [0] = 0.1195
19 val: [0] = 97.4%
[transfer_0] test accuracy = 97.5%
[transfer_0] training getter for step 0:
0 train: [0] = 0.4198
0 train: [0] = 88.5%
0 val: [0] = 0.2139
0 val: [0] = 93.7%
1 train: [0] = 0.1888
1 train: [0] = 94.4%
1 val: [0] = 0.1486
1 val: [0] = 95.5%
2 train: [0] = 0.1342
2 train: [0] = 96.0%
2 val: [0] = 0.1057
2 val: [0] = 96.8%
3 train: [0] = 0.1034
3 train: [0] = 96.9%
3 val: [0] = 0.1167
3 val: [0] = 96.3%
4 train: [0] = 0.08429
4 train: [0] = 97.3%
4 val: [0] = 0.08618
4 val: [0] = 97.4%
5 train: [0] = 0.06891
5 train: [0] = 97.8%
5 val: [0] = 0.09226
5 val: [0] = 97.1%
6 train: [0] = 0.05704
6 train: [0] = 98.2%
6 val: [0] = 0.07795
6 val: [0] = 97.4%
7 train: [0] = 0.04989
7 train: [0] = 98.4%
7 val: [0] = 0.09235
7 val: [0] = 97.1%
8 train: [0] = 0.04206
8 train: [0] = 98.6%
8 val: [0] = 0.0903
8 val: [0] = 97.3%
9 train: [0] = 0.03534
9 train: [0] = 98.9%
9 val: [0] = 0.08237
9 val: [0] = 97.4%
10 train: [0] = 0.03014
10 train: [0] = 99.0%
10 val: [0] = 0.0863
10 val: [0] = 97.5%
11 train: [0] = 0.02738
11 train: [0] = 99.1%
11 val: [0] = 0.0915
11 val: [0] = 97.6%
12 train: [0] = 0.02496
12 train: [0] = 99.2%
12 val: [0] = 0.09104
12 val: [0] = 97.6%
13 train: [0] = 0.02069
13 train: [0] = 99.3%
13 val: [0] = 0.08465
13 val: [0] = 97.7%
14 train: [0] = 0.01721
14 train: [0] = 99.5%
14 val: [0] = 0.09374
14 val: [0] = 97.5%
15 train: [0] = 0.01697
15 train: [0] = 99.4%
15 val: [0] = 0.09494
15 val: [0] = 97.5%
16 train: [0] = 0.0147
16 train: [0] = 99.5%
16 val: [0] = 0.115
16 val: [0] = 97.3%
17 train: [0] = 0.01427
17 train: [0] = 99.5%
17 val: [0] = 0.1092
17 val: [0] = 97.5%
18 train: [0] = 0.01131
18 train: [0] = 99.6%
18 val: [0] = 0.1021
18 val: [0] = 97.5%
19 train: [0] = 0.01269
19 train: [0] = 99.6%
19 val: [0] = 0.1388
19 val: [0] = 97.2%
[transfer_0] test accuracy = 97.0%
[transfer_0] training getter for step 1:
0 train: [0] = 0.4229
0 train: [0] = 88.2%
0 val: [0] = 0.1885
0 val: [0] = 94.7%
1 train: [0] = 0.1893
1 train: [0] = 94.3%
1 val: [0] = 0.1273
1 val: [0] = 96.0%
2 train: [0] = 0.1412
2 train: [0] = 95.7%
2 val: [0] = 0.1053
2 val: [0] = 96.6%
3 train: [0] = 0.1105
3 train: [0] = 96.6%
3 val: [0] = 0.1024
3 val: [0] = 96.8%
4 train: [0] = 0.08959
4 train: [0] = 97.2%
4 val: [0] = 0.09091
4 val: [0] = 97.1%
5 train: [0] = 0.07435
5 train: [0] = 97.6%
5 val: [0] = 0.08502
5 val: [0] = 97.3%
6 train: [0] = 0.0633
6 train: [0] = 98.0%
6 val: [0] = 0.09018
6 val: [0] = 97.1%
7 train: [0] = 0.05559
7 train: [0] = 98.1%
7 val: [0] = 0.09274
7 val: [0] = 97.1%
8 train: [0] = 0.04689
8 train: [0] = 98.5%
8 val: [0] = 0.08366
8 val: [0] = 97.4%
9 train: [0] = 0.04234
9 train: [0] = 98.5%
9 val: [0] = 0.08808
9 val: [0] = 97.4%
10 train: [0] = 0.03563
10 train: [0] = 98.8%
10 val: [0] = 0.08701
10 val: [0] = 97.4%
11 train: [0] = 0.0313
11 train: [0] = 99.0%
11 val: [0] = 0.09485
11 val: [0] = 97.4%
12 train: [0] = 0.02667
12 train: [0] = 99.1%
12 val: [0] = 0.1044
12 val: [0] = 97.1%
13 train: [0] = 0.02385
13 train: [0] = 99.2%
13 val: [0] = 0.09154
13 val: [0] = 97.4%
14 train: [0] = 0.0198
14 train: [0] = 99.4%
14 val: [0] = 0.09491
14 val: [0] = 97.4%
15 train: [0] = 0.02072
15 train: [0] = 99.3%
15 val: [0] = 0.1148
15 val: [0] = 97.1%
16 train: [0] = 0.0181
16 train: [0] = 99.4%
16 val: [0] = 0.1005
16 val: [0] = 97.5%
17 train: [0] = 0.016
17 train: [0] = 99.5%
17 val: [0] = 0.1147
17 val: [0] = 97.3%
18 train: [0] = 0.01414
18 train: [0] = 99.5%
18 val: [0] = 0.1225
18 val: [0] = 97.3%
19 train: [0] = 0.01341
19 train: [0] = 99.6%
19 val: [0] = 0.1184
19 val: [0] = 97.2%
[transfer_0] test accuracy = 96.9%
[transfer_0] training getter for step 2:
0 train: [0] = 0.4096
0 train: [0] = 88.4%
0 val: [0] = 0.1865
0 val: [0] = 94.5%
1 train: [0] = 0.1839
1 train: [0] = 94.5%
1 val: [0] = 0.1323
1 val: [0] = 95.9%
2 train: [0] = 0.1356
2 train: [0] = 95.8%
2 val: [0] = 0.1024
2 val: [0] = 96.8%
3 train: [0] = 0.1061
3 train: [0] = 96.6%
3 val: [0] = 0.09309
3 val: [0] = 97.0%
4 train: [0] = 0.08768
4 train: [0] = 97.2%
4 val: [0] = 0.08509
4 val: [0] = 97.2%
5 train: [0] = 0.07239
5 train: [0] = 97.6%
5 val: [0] = 0.08647
5 val: [0] = 97.1%
6 train: [0] = 0.0613
6 train: [0] = 98.0%
6 val: [0] = 0.08511
6 val: [0] = 97.4%
7 train: [0] = 0.05234
7 train: [0] = 98.3%
7 val: [0] = 0.08117
7 val: [0] = 97.4%
8 train: [0] = 0.04627
8 train: [0] = 98.4%
8 val: [0] = 0.09224
8 val: [0] = 97.1%
9 train: [0] = 0.03877
9 train: [0] = 98.7%
9 val: [0] = 0.08558
9 val: [0] = 97.5%
10 train: [0] = 0.0347
10 train: [0] = 98.8%
10 val: [0] = 0.08661
10 val: [0] = 97.4%
11 train: [0] = 0.03004
11 train: [0] = 99.0%
11 val: [0] = 0.09475
11 val: [0] = 97.5%
12 train: [0] = 0.02461
12 train: [0] = 99.2%
12 val: [0] = 0.08911
12 val: [0] = 97.4%
13 train: [0] = 0.02338
13 train: [0] = 99.2%
13 val: [0] = 0.09759
13 val: [0] = 97.4%
14 train: [0] = 0.01879
14 train: [0] = 99.4%
14 val: [0] = 0.1262
14 val: [0] = 96.8%
15 train: [0] = 0.01983
15 train: [0] = 99.3%
15 val: [0] = 0.113
15 val: [0] = 97.3%
16 train: [0] = 0.01609
16 train: [0] = 99.5%
16 val: [0] = 0.1151
16 val: [0] = 97.2%
17 train: [0] = 0.01506
17 train: [0] = 99.5%
17 val: [0] = 0.1248
17 val: [0] = 97.0%
18 train: [0] = 0.01423
18 train: [0] = 99.5%
18 val: [0] = 0.1285
18 val: [0] = 97.2%
19 train: [0] = 0.01519
19 train: [0] = 99.4%
19 val: [0] = 0.1183
19 val: [0] = 97.3%
[transfer_0] test accuracy = 96.9%
[transfer_0] training getter for step 3:
0 train: [0] = 0.409
0 train: [0] = 88.5%
0 val: [0] = 0.1826
0 val: [0] = 94.3%
1 train: [0] = 0.1815
1 train: [0] = 94.6%
1 val: [0] = 0.1323
1 val: [0] = 95.7%
2 train: [0] = 0.1349
2 train: [0] = 95.8%
2 val: [0] = 0.1008
2 val: [0] = 96.8%
3 train: [0] = 0.1031
3 train: [0] = 96.7%
3 val: [0] = 0.0978
3 val: [0] = 96.9%
4 train: [0] = 0.08439
4 train: [0] = 97.3%
4 val: [0] = 0.08436
4 val: [0] = 97.2%
5 train: [0] = 0.06932
5 train: [0] = 97.7%
5 val: [0] = 0.09006
5 val: [0] = 97.0%
6 train: [0] = 0.06012
6 train: [0] = 98.0%
6 val: [0] = 0.07837
6 val: [0] = 97.4%
7 train: [0] = 0.0515
7 train: [0] = 98.3%
7 val: [0] = 0.08172
7 val: [0] = 97.4%
8 train: [0] = 0.04379
8 train: [0] = 98.6%
8 val: [0] = 0.0837
8 val: [0] = 97.2%
9 train: [0] = 0.0385
9 train: [0] = 98.7%
9 val: [0] = 0.08267
9 val: [0] = 97.3%
10 train: [0] = 0.0327
10 train: [0] = 98.8%
10 val: [0] = 0.0998
10 val: [0] = 97.1%
11 train: [0] = 0.0284
11 train: [0] = 99.0%
11 val: [0] = 0.09311
11 val: [0] = 97.2%
12 train: [0] = 0.02418
12 train: [0] = 99.1%
12 val: [0] = 0.08851
12 val: [0] = 97.3%
13 train: [0] = 0.02288
13 train: [0] = 99.2%
13 val: [0] = 0.09328
13 val: [0] = 97.3%
14 train: [0] = 0.02137
14 train: [0] = 99.2%
14 val: [0] = 0.1108
14 val: [0] = 97.3%
15 train: [0] = 0.01782
15 train: [0] = 99.4%
15 val: [0] = 0.1134
15 val: [0] = 97.4%
16 train: [0] = 0.0167
16 train: [0] = 99.4%
16 val: [0] = 0.1035
16 val: [0] = 97.1%
17 train: [0] = 0.01815
17 train: [0] = 99.4%
17 val: [0] = 0.1081
17 val: [0] = 97.3%
18 train: [0] = 0.01217
18 train: [0] = 99.6%
18 val: [0] = 0.1102
18 val: [0] = 97.3%
19 train: [0] = 0.01121
19 train: [0] = 99.6%
19 val: [0] = 0.1161
19 val: [0] = 97.3%
[transfer_0] test accuracy = 96.8%
[transfer_0] training getter for step 4:
0 train: [0] = 0.4257
0 train: [0] = 87.9%
0 val: [0] = 0.201
0 val: [0] = 94.1%
1 train: [0] = 0.1938
1 train: [0] = 94.3%
1 val: [0] = 0.1388
1 val: [0] = 95.8%
2 train: [0] = 0.1378
2 train: [0] = 95.8%
2 val: [0] = 0.1024
2 val: [0] = 96.9%
3 train: [0] = 0.1077
3 train: [0] = 96.7%
3 val: [0] = 0.09369
3 val: [0] = 97.1%
4 train: [0] = 0.08791
4 train: [0] = 97.1%
4 val: [0] = 0.08574
4 val: [0] = 97.2%
5 train: [0] = 0.07147
5 train: [0] = 97.6%
5 val: [0] = 0.09088
5 val: [0] = 97.1%
6 train: [0] = 0.05912
6 train: [0] = 98.0%
6 val: [0] = 0.09007
6 val: [0] = 97.1%
7 train: [0] = 0.05131
7 train: [0] = 98.3%
7 val: [0] = 0.0866
7 val: [0] = 97.1%
8 train: [0] = 0.04317
8 train: [0] = 98.5%
8 val: [0] = 0.09975
8 val: [0] = 96.9%
9 train: [0] = 0.03665
9 train: [0] = 98.8%
9 val: [0] = 0.07756
9 val: [0] = 97.5%
10 train: [0] = 0.03097
10 train: [0] = 98.9%
10 val: [0] = 0.09151
10 val: [0] = 97.2%
11 train: [0] = 0.02686
11 train: [0] = 99.1%
11 val: [0] = 0.08784
11 val: [0] = 97.3%
12 train: [0] = 0.02571
12 train: [0] = 99.1%
12 val: [0] = 0.09105
12 val: [0] = 97.4%
13 train: [0] = 0.02028
13 train: [0] = 99.3%
13 val: [0] = 0.1081
13 val: [0] = 97.1%
14 train: [0] = 0.01993
14 train: [0] = 99.3%
14 val: [0] = 0.103
14 val: [0] = 97.1%
15 train: [0] = 0.01709
15 train: [0] = 99.4%
15 val: [0] = 0.1044
15 val: [0] = 97.3%
16 train: [0] = 0.01626
16 train: [0] = 99.5%
16 val: [0] = 0.1242
16 val: [0] = 97.2%
17 train: [0] = 0.01617
17 train: [0] = 99.4%
17 val: [0] = 0.1308
17 val: [0] = 96.9%
18 train: [0] = 0.01351
18 train: [0] = 99.6%
18 val: [0] = 0.1164
18 val: [0] = 97.1%
19 train: [0] = 0.01272
19 train: [0] = 99.6%
19 val: [0] = 0.1152
19 val: [0] = 97.3%
[transfer_0] test accuracy = 96.6%
