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imagenet-sweep-vanilla-x64-CLS_3-hook_resid_post-686.334411621094-95 – AI Model by Prisma-Multimodal | AlphaNeural AI
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imagenet-sweep-vanilla-x64-CLS_3-hook_resid_post-686.334411621094-95
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CLIP Sparse Autoencoder Checkpoint
This model is a sparse autoencoder trained on CLIP's internal representations.
Model Details
Architecture
Layer
: 3
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
: True
Training
Training Images
: 1298432
Learning Rate
: 0.0130
L1 Coefficient
: 0.0000
Batch Size
: 4096
Context Size
: 1
Performance Metrics
Sparsity
L0 (Active Features)
: 686.3344
Dead Features
: 0
Mean Passes Since Fired
: 284.3346
Reconstruction
Explained Variance
: 0.9568
Explained Variance Std
: 0.0149
MSE Loss
: 0.0001
L1 Loss
: 144.6529
Overall Loss
: 0.0001
Training Details
Training Duration
: 264 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/d422fbb4-tinyclip_sae_16_hyperparam_sweep_lr/n_images_1302528.pt
Wandb Run
:
https://wandb.ai/perceptual-alignment/vanilla-imagenet-CLS_only-sweep/runs/8db8ohpb
Random Seed
: 42
