Test about mi-eeg-1d-cnn

[ambitious-octopus]

Results first two seconds.

Epoch 29/30
22031/22032 [============================>.] - ETA: 0s - loss: 0.3579 - accuracy: 0.8734  
Epoch 00029: val_loss did not improve from 0.20494
22032/22032 [==============================] - 73s 3ms/step - loss: 0.3579 - accuracy: 0.8734 - val_loss: 0.2107 - val_accuracy: 0.9565
Epoch 30/30
22024/22032 [============================>.] - ETA: 0s - loss: 0.3539 - accuracy: 0.8752  
Epoch 00030: val_loss improved from 0.20494 to 0.19900, saving model to /workspace/bestModel.h5
22032/22032 [==============================] - 73s 3ms/step - loss: 0.3539 - accuracy: 0.8752 - val_loss: 0.1990 - val_accuracy: 0.9556
344/344 [==============================] - 13s 38ms/step - loss: 0.2087 - accuracy: 0.9532

Accuracy: 0.9531775712966919

Loss:  0.20874853432178497

[ambitious-octopus]

Results last two seconds.

Epoch 30/30
22026/22032 [============================>.] - ETA: 0s - loss: 0.3502 - accuracy: 0.8766  
Epoch 00030: val_loss did not improve from 0.20552
22032/22032 [==============================] - 80s 4ms/step - loss: 0.3501 - accuracy: 0.8766 - val_loss: 0.2125 - val_accuracy: 0.9523
344/344 [==============================] - 16s 47ms/step - loss: 0.2094 - accuracy: 0.9539

Accuracy: 0.953904926776886

Loss:  0.20941005647182465

[ambitious-octopus]

Both:

13767/13770 [============================>.] - ETA: 0s - loss: 0.6190 - accuracy: 0.7690 
Epoch 00060: val_loss did not improve from 0.53824
13770/13770 [==============================] - 43s 3ms/step - loss: 0.6190 - accuracy: 0.7690 - val_loss: 0.5501 - val_accuracy: 0.8790
688/688 [==============================] - 15s 22ms/step - loss: 0.5407 - accuracy: 0.8760

Accuracy: 0.8759887218475342

Loss:  0.5407426357269287

[ambitious-octopus]

1 Second window:

Epoch 17/100
27529/27540 [============================>.] - ETA: 0s - loss: 1.4640 - accuracy: 0.3384  
Epoch 00017: val_accuracy did not improve from 0.50064
27540/27540 [==============================] - 86s 3ms/step - loss: 1.4640 - accuracy: 0.3384 - val_loss: 1.4490 - val_accuracy: 0.5002
1375/1375 [==============================] - 23s 17ms/step - loss: 1.4490 - accuracy: 0.5004

Accuracy: 0.5003523230552673

Loss:  1.449002742767334