Row 7366

Row ID: 7366 | Dataset Entry | Axioma AXP Content Repository

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Hi everyone,

I'm currently working on a project where I use a VAE to perform inverse design of 3D models (voxels comprised of 1s and 0s). Below, I've attached an image of my loss curve. It seems that model is overfitting when it comes to reconstruction loss, but does well with KL loss. Any suggestions for how I can improve the reconstruction loss?

Also my loss values are to the scale of 1e6, I'm not sure if this is necessarily a bad thing, but the images generated from the model aren't terrible.

https://preview.redd.it/phoqiit5no0d1.png?width=1719&format=png&auto=webp&s=a33a7a0468548bf180c81ff506db96e0a91fd557

For further context, I am using convolutional layers for upsampling and downsampling. I've added KL annealing and a learning rate scheduler. Also, I use BCE loss for my reconstruction loss, I tried MSE loss but performance was worse and it didn't really make sense since the models are binary not continuous.

I appreciate any suggestions!

FieldValue
text Hi everyone, I'm currently working on a project where I use a VAE to perform inverse design of 3D models (voxels comprised of 1s and 0s). Below, I've attached an image of my loss curve. It seems that model is overfitting when it comes to reconstruction loss, but does well with KL loss. Any suggestions for how I can improve the reconstruction loss? Also my loss values are to the scale of 1e6, I'm not sure if this is necessarily a bad thing, but the images generated from the model aren't terribl…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-16
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Raw Record

{
  "text": "Hi everyone,\n\nI'm currently working on a project where I use a VAE to perform inverse design of 3D models (voxels comprised of 1s and 0s). Below, I've attached an image of my loss curve. It seems that model is overfitting when it comes to reconstruction loss, but does well with KL loss. Any suggestions for how I can improve the reconstruction loss?\n\nAlso my loss values are to the scale of 1e6, I'm not sure if this is necessarily a bad thing, but the images generated from the model aren't terrible.\n\nhttps://preview.redd.it/phoqiit5no0d1.png?width=1719&format=png&auto=webp&s=a33a7a0468548bf180c81ff506db96e0a91fd557\n\nFor further context, I am using convolutional layers for upsampling and downsampling. I've added KL annealing and a learning rate scheduler. Also, I use BCE loss for my reconstruction loss, I tried MSE loss but performance was worse and it didn't really make sense since the models are binary not continuous.\n\nI appreciate any suggestions!",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-16",
  "username_encoded": "Z0FBQUFBQm5LakwzMDBRY3c0X0R3UlNTXzI1OE1hOXpMUVhiajZqcTJKQkliZ0MwWGpPQ3BQdDJ4TG1FaW9GanFUa1MtQ2xXU3h6cGowREVJcUo2QWtiaTF4aWFCY1lHWlE9PQ==",
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}
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