# CLIP Sparse Autoencoder Checkpoint

This model is a sparse autoencoder trained on CLIP's internal representations.

## Model Details

### Architecture
- **Layer**: 11
- **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**: False

### Training
- **Training Images**: 1299936
- **Learning Rate**: 0.0001
- **L1 Coefficient**: 0.0000
- **Batch Size**: 4096
- **Context Size**: 49

## Performance Metrics

### Sparsity
- **L0 (Active Features)**: 1044.9467
- **Dead Features**: 0

- **Mean Passes Since Fired**: 0.4841

### Reconstruction
- **Explained Variance**: 0.9630
- **Explained Variance Std**: 0.0562
- **MSE Loss**: 0.0010
- **L1 Loss**: 558.9109
- **Overall Loss**: 0.0033

## Training Details
- **Training Duration**: 6336 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/ec15906c-tinyclip_sae_16_hyperparam_sweep_lr/n_images_1300020.pt
- **Wandb Run**: https://wandb.ai/perceptual-alignment/vanilla-imagenet-spatial_only-sweep/runs/9cl93riz
- **Random Seed**: 42