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Update README - Run 20251012_210041

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  1. README.md +16 -19
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  type: imagenet-1k
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  metrics:
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  - type: accuracy
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- value: 75.74
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  ---
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  # David: Multi-Scale Feature Classifier
@@ -45,25 +45,22 @@ exist simultaneously in the same shared space with the correct checks and spacin
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  ### Training Configuration
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  - **Dataset**: AbstractPhil/imagenet-clip-features-orderly
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- - **Model Variant**: ['clip_vit_b16', 'clip_vit_laion_b32']
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  - **Epochs**: 10
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  - **Batch Size**: 1024
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  - **Learning Rate**: 0.01
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  - **Rose Loss Weight**: 0.2 β†’ 0.8
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- - **Cayley Loss**: True
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  ## Performance
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  ### Best Results
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- - **Validation Accuracy**: 75.74%
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- - **Best Epoch**: 9
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- - **Final Train Accuracy**: 83.82%
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  ### Per-Scale Performance
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- - **Scale 256**: 74.18%
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- - **Scale 512**: 75.73%
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- - **Scale 768**: 76.05%
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- - **Scale 1024**: 76.08%
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  ## Usage
@@ -81,18 +78,18 @@ AbstractPhil/david-shared-space/
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  β”œβ”€β”€ best_model.json # Latest best model info
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  β”œβ”€β”€ weights/
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  β”‚ └── david_balanced/
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- β”‚ └── 20251012_194945/
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  β”‚ β”œβ”€β”€ MODEL_SUMMARY.txt # 🎯 Human-readable performance summary
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  β”‚ β”œβ”€β”€ training_history.json # πŸ“ˆ Epoch-by-epoch training curve
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- β”‚ β”œβ”€β”€ best_model_acc75.74.safetensors # ⭐ Accuracy in filename!
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- β”‚ β”œβ”€β”€ best_model_acc75.74_metadata.json
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  β”‚ β”œβ”€β”€ final_model.safetensors
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  β”‚ β”œβ”€β”€ checkpoint_epoch_X_accYY.YY.safetensors
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  β”‚ β”œβ”€β”€ david_config.json
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  β”‚ └── train_config.json
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  └── runs/
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  └── david_balanced/
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- └── 20251012_194945/
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  └── events.out.tfevents.* # TensorBoard logs
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  ```
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@@ -106,8 +103,8 @@ from huggingface_hub import hf_hub_download
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  # Specify model variant and run
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  model_name = "david_balanced"
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- run_id = "20251012_194945"
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- accuracy = "75.74" # From MODELS_INDEX.json
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  # Download config
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  config_path = hf_hub_download(
@@ -184,7 +181,7 @@ score = w_anchor * sim(z, anchor) + w_need * sim(z, need) + ...
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  ### Loss Components
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  - **Cross-Entropy**: Standard classification loss
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  - **Rose Loss**: Pentachora role-weighted margin loss (weight: 0.2β†’0.8)
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- - **Cayley Loss**: Geometric regularization (enabled)
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  ### Optimization
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  - **Optimizer**: AdamW
@@ -201,7 +198,7 @@ score = w_anchor * sim(z, anchor) + w_need * sim(z, need) + ...
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  author = {AbstractPhil},
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  year = {2025},
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  url = {https://huggingface.co/AbstractPhil/david-shared-space},
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- note = {Run ID: 20251012_194945}
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  }
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  ```
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@@ -216,4 +213,4 @@ Special thanks to Claude (Anthropic) for debugging assistance.
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  ---
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- *Generated on 2025-10-12 20:21:47*
 
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  type: imagenet-1k
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  metrics:
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  - type: accuracy
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+ value: 66.43
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  ---
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  # David: Multi-Scale Feature Classifier
 
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  ### Training Configuration
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  - **Dataset**: AbstractPhil/imagenet-clip-features-orderly
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+ - **Model Variant**: ['clip_vit_b16', 'clip_vit_laion_b32', 'clip_vit_b32']
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  - **Epochs**: 10
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  - **Batch Size**: 1024
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  - **Learning Rate**: 0.01
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  - **Rose Loss Weight**: 0.2 β†’ 0.8
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+ - **Cayley Loss**: False
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  ## Performance
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  ### Best Results
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+ - **Validation Accuracy**: 66.43%
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+ - **Best Epoch**: 0
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+ - **Final Train Accuracy**: 56.12%
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  ### Per-Scale Performance
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+ - **Scale 256**: 66.43%
 
 
 
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  ## Usage
 
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  β”œβ”€β”€ best_model.json # Latest best model info
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  β”œβ”€β”€ weights/
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  β”‚ └── david_balanced/
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+ β”‚ └── 20251012_210041/
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  β”‚ β”œβ”€β”€ MODEL_SUMMARY.txt # 🎯 Human-readable performance summary
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  β”‚ β”œβ”€β”€ training_history.json # πŸ“ˆ Epoch-by-epoch training curve
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+ β”‚ β”œβ”€β”€ best_model_acc66.43.safetensors # ⭐ Accuracy in filename!
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+ β”‚ β”œβ”€β”€ best_model_acc66.43_metadata.json
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  β”‚ β”œβ”€β”€ final_model.safetensors
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  β”‚ β”œβ”€β”€ checkpoint_epoch_X_accYY.YY.safetensors
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  β”‚ β”œβ”€β”€ david_config.json
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  β”‚ └── train_config.json
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  └── runs/
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  └── david_balanced/
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+ └── 20251012_210041/
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  └── events.out.tfevents.* # TensorBoard logs
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  ```
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  # Specify model variant and run
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  model_name = "david_balanced"
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+ run_id = "20251012_210041"
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+ accuracy = "66.43" # From MODELS_INDEX.json
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  # Download config
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  config_path = hf_hub_download(
 
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  ### Loss Components
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  - **Cross-Entropy**: Standard classification loss
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  - **Rose Loss**: Pentachora role-weighted margin loss (weight: 0.2β†’0.8)
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+ - **Cayley Loss**: Geometric regularization (disabled)
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  ### Optimization
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  - **Optimizer**: AdamW
 
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  author = {AbstractPhil},
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  year = {2025},
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  url = {https://huggingface.co/AbstractPhil/david-shared-space},
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+ note = {Run ID: 20251012_210041}
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  }
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  ```
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  ---
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+ *Generated on 2025-10-12 21:05:14*