Comments (3)
Downloading the fer2013.csv and splitting it into train.csv and test.csv (80/20 proportion) worked for me
from deep-emotion.
When I train this network, the loss function and accuracy remain unchanged.
Epoch: 1 Training Loss: 0.01437178 Validation Loss 0.01457405 Training Acuuarcy 24.926% Validation Acuuarcy 24.937%
Epoch: 2 Training Loss: 0.01419203 Validation Loss 0.01462503 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 3 Training Loss: 0.01419188 Validation Loss 0.01466722 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 4 Training Loss: 0.01419332 Validation Loss 0.01468434 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 5 Training Loss: 0.01419407 Validation Loss 0.01456469 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 6 Training Loss: 0.01419189 Validation Loss 0.01469155 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 7 Training Loss: 0.01419034 Validation Loss 0.01467826 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 8 Training Loss: 0.01419431 Validation Loss 0.01466055 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 9 Training Loss: 0.01418729 Validation Loss 0.01462144 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 10 Training Loss: 0.01418980 Validation Loss 0.01466851 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 11 Training Loss: 0.01419380 Validation Loss 0.01461501 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 12 Training Loss: 0.01418736 Validation Loss 0.01464282 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 13 Training Loss: 0.01418842 Validation Loss 0.01461904 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 14 Training Loss: 0.01418909 Validation Loss 0.01475997 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 15 Training Loss: 0.01418691 Validation Loss 0.01454415 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 16 Training Loss: 0.01419212 Validation Loss 0.01459282 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 17 Training Loss: 0.01419064 Validation Loss 0.01479096 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 18 Training Loss: 0.01418800 Validation Loss 0.01460306 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 19 Training Loss: 0.01418691 Validation Loss 0.01465107 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 20 Training Loss: 0.01418918 Validation Loss 0.01462860 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 21 Training Loss: 0.01419190 Validation Loss 0.01458804 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 22 Training Loss: 0.01418829 Validation Loss 0.01460765 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 23 Training Loss: 0.01418722 Validation Loss 0.01455541 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 24 Training Loss: 0.01418603 Validation Loss 0.01469193 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 25 Training Loss: 0.01418951 Validation Loss 0.01463459 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 26 Training Loss: 0.01418810 Validation Loss 0.01476145 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 27 Training Loss: 0.01418882 Validation Loss 0.01468886 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 28 Training Loss: 0.01419031 Validation Loss 0.01463278 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 29 Training Loss: 0.01418738 Validation Loss 0.01465452 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
from deep-emotion.
When I train this network, the loss function and accuracy remain unchanged.
Epoch: 1 Training Loss: 0.01437178 Validation Loss 0.01457405 Training Acuuarcy 24.926% Validation Acuuarcy 24.937%
Epoch: 2 Training Loss: 0.01419203 Validation Loss 0.01462503 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 3 Training Loss: 0.01419188 Validation Loss 0.01466722 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 4 Training Loss: 0.01419332 Validation Loss 0.01468434 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 5 Training Loss: 0.01419407 Validation Loss 0.01456469 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 6 Training Loss: 0.01419189 Validation Loss 0.01469155 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 7 Training Loss: 0.01419034 Validation Loss 0.01467826 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 8 Training Loss: 0.01419431 Validation Loss 0.01466055 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 9 Training Loss: 0.01418729 Validation Loss 0.01462144 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 10 Training Loss: 0.01418980 Validation Loss 0.01466851 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 11 Training Loss: 0.01419380 Validation Loss 0.01461501 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 12 Training Loss: 0.01418736 Validation Loss 0.01464282 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 13 Training Loss: 0.01418842 Validation Loss 0.01461904 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 14 Training Loss: 0.01418909 Validation Loss 0.01475997 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 15 Training Loss: 0.01418691 Validation Loss 0.01454415 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 16 Training Loss: 0.01419212 Validation Loss 0.01459282 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 17 Training Loss: 0.01419064 Validation Loss 0.01479096 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 18 Training Loss: 0.01418800 Validation Loss 0.01460306 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 19 Training Loss: 0.01418691 Validation Loss 0.01465107 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 20 Training Loss: 0.01418918 Validation Loss 0.01462860 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 21 Training Loss: 0.01419190 Validation Loss 0.01458804 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 22 Training Loss: 0.01418829 Validation Loss 0.01460765 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 23 Training Loss: 0.01418722 Validation Loss 0.01455541 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 24 Training Loss: 0.01418603 Validation Loss 0.01469193 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 25 Training Loss: 0.01418951 Validation Loss 0.01463459 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 26 Training Loss: 0.01418810 Validation Loss 0.01476145 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 27 Training Loss: 0.01418882 Validation Loss 0.01468886 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 28 Training Loss: 0.01419031 Validation Loss 0.01463278 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
Epoch: 29 Training Loss: 0.01418738 Validation Loss 0.01465452 Training Acuuarcy 25.131% Validation Acuuarcy 24.937%
try to follow the readme and also it might help to read this comment #6 (comment)
from deep-emotion.
Related Issues (17)
- where is the pretrained model HOT 3
- Target 3579 is out of bounds
- Test dataset
- raise KeyError(key) from err KeyError: 'emotion' HOT 1
- Why the loss function is not same with paper said? HOT 1
- accuracy HOT 3
- Request for the pre-trained model
- Kindly share a pretrained model / a .pt file HOT 1
- Grid Generation
- Request for JAFFE metafile HOT 2
- Are the pre-trained models available? HOT 5
- Question about hyperparameters HOT 9
- Question about the code about model HOT 6
- How to run the model on CK+? HOT 1
- . HOT 1
- Questions about confusion matrix
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from deep-emotion.