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sae-top_k-64-cls_only-layer_4-hook_resid_post – AI Model by Prisma-Multimodal | AlphaNeural AI
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sae-top_k-64-cls_only-layer_4-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
: 4
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
: 171618304
Learning Rate
: 0.0002
L1 Coefficient
: 0.3000
Batch Size
: 4096
Context Size
: 1
Performance Metrics
Sparsity
L0 (Active Features)
: 64
Dead Features
: 27636
Mean Log10 Feature Sparsity
: -9.1191
Features Below 1e-5
: 48474
Features Below 1e-6
: 39986
Mean Passes Since Fired
: 14514.3223
Reconstruction
Explained Variance
: 0.9411
Explained Variance Std
: 0.0165
MSE Loss
: 0.0001
L1 Loss
: 0
Overall Loss
: 0.0001
Training Details
Training Duration
: 17915.6712 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/bqv5jw5n
Original Checkpoint Path
: /network/scratch/s/sonia.joseph/checkpoints/clip-b
Random Seed
: 42
