Optuna example (fastai v2): is the example maximizing validation loss ? about optuna-examples HOT 4 CLOSED

|epoch | train_loss | valid_loss | accuracy | time|
|--- | --- | --- | --- | ---|
|0 | 0.471152 | 0.213294 | 0.959274 | 00:03|
|1 | 0.251552 | 0.085383 | 0.985770 | 00:03|
|2 | 0.126371 | 0.055183 | 0.988224 | 00:03|
|3 | 0.076224 | 0.039957 | 0.990186 | 00:03|
|4 | 0.056587 | 0.030830 | 0.990677 | 00:03|
|5 | 0.047404 | 0.023672 | 0.993131 | 00:03|
|6 | 0.039950 | 0.022306 | 0.992149 | 00:03|
|7 | 0.041833 | 0.020039 | 0.993621 | 00:03|
|8 | 0.035657 | 0.018003 | 0.993131 | 00:03|
|9 | 0.030431 | 0.015924 | 0.995093 | 00:03|


[I 2021-06-23 16:54:52,062] Trial 0 finished with value: 0.9950932264328003 and parameters: {'apply_tfms': True, 'max_rotate': 1, 'max_zoom': 1.242046338907775, 'p_affine': 0.7000000000000001, 'n_layers': 5, 'n_channels_0': 4, 'n_channels_1': 9, 'n_channels_2': 11, 'n_channels_3': 9, 'n_channels_4': 21}. Best is trial 0 with value: 0.9950932264328003.

epoch    train_loss    valid_loss    accuracy    time
0    0.391116    0.158786    0.964181    00:03
1    0.255199    0.098080    0.971541    00:03
2    0.208814    0.077618    0.975957    00:03
3    0.178489    0.066051    0.980373    00:03
4    0.158369    0.061916    0.978901    00:03
5    0.146922    0.060670    0.984298    00:03
6    0.137263    0.062824    0.975957    00:03
7    0.130735    0.044604    0.986752    00:03
8    0.124975    0.048074    0.990186    00:03
9    0.120322    0.056707    0.979392    00:03

[I 2021-06-23 16:55:32,077] Trial 1 finished with value: 0.9793915748596191 and parameters: {'apply_tfms': True, 'max_rotate': 32, 'max_zoom': 1.6189198430838707, 'p_affine': 0.30000000000000004, 'n_layers': 2, 'n_channels_0': 22, 'n_channels_1': 15}. Best is trial 0 with value: 0.9950932264328003.


|epoch | train_loss | valid_loss | accuracy | time|
|--- | --- | --- | --- | ---|
|0 | 0.189745 | 0.113877 | 0.960746 | 00:02|

[I 2021-06-23 16:55:36,113] Trial 2 pruned. Trial was pruned at epoch 0.


|epoch | train_loss | valid_loss | accuracy | time|
|--- | --- | --- | --- | ---|
|0 | 0.483240 | 0.227257 | 0.973013 | 00:03|
|1 | 0.267175 | 0.114635 | 0.980864 | 00:03|
|2 | 0.154494 | 0.062144 | 0.990677 | 00:03|
|3 | 0.103251 | 0.037902 | 0.991168 | 00:03|
|4 | 0.083039 | 0.037244 | 0.992640 | 00:03|
|5 | 0.070180 | 0.028697 | 0.991168 | 00:03|
|6 | 0.059144 | 0.024078 | 0.993131 | 00:03|
|7 | 0.055209 | 0.022824 | 0.993131 | 00:03|
|8 | 0.052700 | 0.020156 | 0.994112 | 00:03|
|9 | 0.046110 | 0.023263 | 0.991659 | 00:03|

[I 2021-06-23 16:56:12,867] Trial 3 finished with value: 0.9916585087776184 and parameters: {'apply_tfms': True, 'max_rotate': 45, 'max_zoom': 1.0501142679315925, 'p_affine': 0.8, 'n_layers': 5, 'n_channels_0': 16, 'n_channels_1': 6, 'n_channels_2': 10, 'n_channels_3': 13, 'n_channels_4': 16}. Best is trial 0 with value: 0.9950932264328003.