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sae-top_k-64-cls_only-layer_1-hook_resid_post – AI Model by Prisma-Multimodal | AlphaNeural AI
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sae-top_k-64-cls_only-layer_1-hook_resid_post
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CLIP Sparse Autoencoder Checkpoint
This model is a sparse autoencoder trained on CLIP's internal representations.
Model Details
Architecture
Layer
: 1
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
: 206843904
Learning Rate
: 0.0002
L1 Coefficient
: 0.3000
Batch Size
: 4096
Context Size
: 1
Performance Metrics
Sparsity
L0 (Active Features)
: 64
Dead Features
: 29224
Mean Log10 Feature Sparsity
: -9.3313
Features Below 1e-5
: 48808
Features Below 1e-6
: 42124
Mean Passes Since Fired
: 15533.3896
Reconstruction
Explained Variance
: 0.9689
Explained Variance Std
: 0.0180
MSE Loss
: 0.0000
L1 Loss
: 0
Overall Loss
: 0.0000
Training Details
Training Duration
: 17941.6724 seconds
Final Learning Rate
: 0.0002
Warm Up Steps
: 200
Gradient Clipping
: 1
Additional Information
Weights & Biases Run
:
https://wandb.ai/perceptual-alignment/clip/runs/yrtlmomi
Original Checkpoint Path
: /network/scratch/s/sonia.joseph/checkpoints/clip-b
Random Seed
: 42
