*****************************************************************
Epoch: 02316
Training cost: 0.055
Training accuracy: 0.9833
Valid cost: 1.68
Valid_UA: 0.4966
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 6 37 9 21]
[15 9 6 26]
[33 26 19 73]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 02481
Training cost: 0.0198
Training accuracy: 1
Valid cost: 1.9
Valid_UA: 0.5329
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 3 40 14 16]
[11 9 20 16]
[29 24 47 51]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
*****************************************************************
Epoch: 03201
Training cost: 0.00939
Training accuracy: 1
Valid cost: 2.16
Valid_UA: 0.5066
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 5 37 13 18]
[11 9 19 17]
[38 24 45 44]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03206
Training cost: 0.00857
Training accuracy: 1
Valid cost: 2.17
Valid_UA: 0.5135
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 5 39 13 16]
[11 9 19 17]
[37 24 46 44]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03211
Training cost: 0.00816
Training accuracy: 1
Valid cost: 2.18
Valid_UA: 0.5118
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 6 39 13 15]
[11 9 19 17]
[38 23 47 43]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03216
Training cost: 0.00737
Training accuracy: 1
Valid cost: 2.17
Valid_UA: 0.4987
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 5 36 13 19]
[11 9 18 18]
[38 23 46 44]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03221
Training cost: 0.00923
Training accuracy: 1
Valid cost: 2.17
Valid_UA: 0.5066
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 6 37 13 17]
[11 9 19 17]
[39 23 45 44]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03226
Training cost: 0.00843
Training accuracy: 1
Valid cost: 2.18
Valid_UA: 0.5135
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 6 39 13 15]
[11 9 19 17]
[38 24 45 44]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************
*****************************************************************
Epoch: 03231
Training cost: 0.00802
Training accuracy: 1
Valid cost: 2.18
Valid_UA: 0.5118
Best valid_UA: 0.6268
Valid Confusion Matrix:["ang","sad","hap","neu"]
[[16 0 1 1]
[ 6 39 13 15]
[11 9 19 17]
[39 23 46 43]]
Best Valid Confusion Matrix:["ang","sad","hap","neu"]
[[17 0 1 0]
[ 1 43 11 18]
[ 6 6 23 21]
[14 23 29 85]]
*****************************************************************