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README.md
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# CLIP Sparse Autoencoder Checkpoint
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This model is a sparse autoencoder trained on CLIP's internal representations.
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## Model Details
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### Architecture
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- **Layer**: 3
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- **Layer Type**: hook_resid_post
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- **Model**: open-clip:laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K
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- **Dictionary Size**: 49152
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- **Input Dimension**: 768
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- **Expansion Factor**: 64
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- **CLS Token Only**: True
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### Training
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- **Training Images**: 183087104
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- **Learning Rate**: 0.0002
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- **L1 Coefficient**: 0.3000
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- **Batch Size**: 4096
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- **Context Size**: 1
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## Performance Metrics
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### Sparsity
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- **L0 (Active Features)**: 64
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- **Dead Features**: 29335
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- **Mean Log10 Feature Sparsity**: -9.2914
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- **Features Below 1e-5**: 48859
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- **Features Below 1e-6**: 41691
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- **Mean Passes Since Fired**: 16714.2930
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### Reconstruction
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- **Explained Variance**: 0.9595
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- **Explained Variance Std**: 0.0150
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- **MSE Loss**: 0.0001
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- **L1 Loss**: 0
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- **Overall Loss**: 0.0001
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## Training Details
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- **Training Duration**: 17942.3141 seconds
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- **Final Learning Rate**: 0.0002
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- **Warm Up Steps**: 200
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- **Gradient Clipping**: 1
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## Additional Information
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- **Weights & Biases Run**: https://wandb.ai/perceptual-alignment/clip/runs/34j4mtdy
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- **Original Checkpoint Path**: /network/scratch/s/sonia.joseph/checkpoints/clip-b
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- **Random Seed**: 42
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