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imagenet-sweep-vanilla-x64-Spatial_max_2-hook_resid_post-1007.89801025391-99 – AI Model by Prisma-Multimodal | AlphaNeural AI
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imagenet-sweep-vanilla-x64-Spatial_max_2-hook_resid_post-1007.89801025391-99
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CLIP Sparse Autoencoder Checkpoint
This model is a sparse autoencoder trained on CLIP's internal representations.
Model Details
Architecture
Layer
: 2
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
: 0.0028
L1 Coefficient
: 0.0000
Batch Size
: 4096
Context Size
: 49
Performance Metrics
Sparsity
L0 (Active Features)
: 1007.8980
Dead Features
: 0
Mean Passes Since Fired
: 110.7943
Reconstruction
Explained Variance
: 1.0000
Explained Variance Std
: 0.0001
MSE Loss
: 0.0000
L1 Loss
: 1889.8757
Overall Loss
: 0.0000
Training Details
Training Duration
: 4521 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/07919f94-tinyclip_sae_16_hyperparam_sweep_lr/n_images_1300020.pt
Wandb Run
:
https://wandb.ai/perceptual-alignment/vanilla-imagenet-Spatial_only-012-sweep/runs/4rza7roh
Random Seed
: 42
