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imagenet-sweep-vanilla-x64-Spatial_9-hook_resid_post-1875.71850585938-95 – AI Model by Prisma-Multimodal | AlphaNeural AI
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Prisma-Multimodal
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imagenet-sweep-vanilla-x64-Spatial_9-hook_resid_post-1875.71850585938-95
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CLIP Sparse Autoencoder Checkpoint
This model is a sparse autoencoder trained on CLIP's internal representations.
Model Details
Architecture
Layer
: 9
Layer Type
: hook_resid_post
Model
: open-clip:laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K
Dictionary Size
: 49152
Input Dimension
: 768
Expansion Factor
: 64
CLS Token Only
: False
Training
Training Images
: 1299936
Learning Rate
: 0.0019
L1 Coefficient
: 0.0000
Batch Size
: 4096
Context Size
: 49
Performance Metrics
Sparsity
L0 (Active Features)
: 1875.7185
Dead Features
: 0
Mean Passes Since Fired
: 0.6052
Reconstruction
Explained Variance
: 0.9558
Explained Variance Std
: 0.0106
MSE Loss
: 0.0010
L1 Loss
: 194.2732
Overall Loss
: 0.0032
Training Details
Training Duration
: 4023 seconds
Final Learning Rate
: 0.0000
Warm Up Steps
: 200
Gradient Clipping
: 1
Additional Information
Original Checkpoint Path
: /network/scratch/p/praneet.suresh/imgnet_checkpoints/8cc43325-tinyclip_sae_16_hyperparam_sweep_lr/n_images_1300020.pt
Wandb Run
:
https://wandb.ai/perceptual-alignment/vanilla-imagenet-spatial_only-sweep/runs/9tklirj1
Random Seed
: 42
