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imagenet-sweep-vanilla-x64-Spatial_max_4-hook_resid_post-965.410095214844-99 – AI Model by Prisma-Multimodal | AlphaNeural AI
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imagenet-sweep-vanilla-x64-Spatial_max_4-hook_resid_post-965.410095214844-99
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CLIP Sparse Autoencoder Checkpoint
This model is a sparse autoencoder trained on CLIP's internal representations.
Model Details
Architecture
Layer
: 4
Layer Type
: hook_resid_post
Model
: open-clip:laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K
Dictionary Size
: 49152.0
Input Dimension
: 768.0
Expansion Factor
: 64.0
CLS Token Only
: False
Training
Training Images
: 1299936.0000
Learning Rate
: 0.0002
L1 Coefficient
: 0.0000
Batch Size
: 4096.0
Context Size
: 49.0
Performance Metrics
Sparsity
L0 (Active Features)
: 965.4101
Dead Features
: 0.0000
Mean Passes Since Fired
: 2.1601
Reconstruction
Explained Variance
: 0.9987
Explained Variance Std
: 0.0032
MSE Loss
: 0.0000
L1 Loss
: 1456.6568
Overall Loss
: 0.0001
Training Details
Training Duration
: 3927 seconds
Final Learning Rate
: 0.0000
Warm Up Steps
: 200.0
Gradient Clipping
: 1.0
Additional Information
Original Checkpoint Path
: /network/scratch/p/praneet.suresh/imgnet_checkpoints/c8de8491-tinyclip_sae_16_hyperparam_sweep_lr/n_images_1300020.pt
Wandb Run
:
https://wandb.ai/perceptual-alignment/vanilla-imagenet-spatial_only-sweep/runs/7dfdq3cz
Random Seed
: 42.0
