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Update beatrix-4simplex-45d_20251007_231008 - Epoch 0 - Acc: 0.0546

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README.md CHANGED
@@ -45,41 +45,42 @@ When train accuracy exceeds validation accuracy by 2% or more, the system automa
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  | beatrix-cifar100 | 20251007_195812 | 0.4701 | 42 | `weights/beatrix-cifar100/20251007_195812` | `logs/beatrix-cifar100/20251007_195812` |
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  | beatrix-cifar100 | 20251007_203741 | 0.4324 | 40 | `weights/beatrix-cifar100/20251007_203741` | `logs/beatrix-cifar100/20251007_203741` |
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  | beatrix-cifar100 | 20251007_193112 | 0.2802 | 10 | `weights/beatrix-cifar100/20251007_193112` | `N/A` |
 
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- ## Latest Updated Model: beatrix-cifar100 (Session: 20251007_215344)
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  ### Model Details
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  - **Architecture**: Vision Transformer with fractal positional encoding
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  - **Dataset**: CIFAR-100 (100 classes)
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- - **Embedding Dimension**: 512
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- - **Depth**: 12 layers
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  - **Patch Size**: 4x4
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  - **PE Levels**: 12
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- - **Simplex Dimension**: 5-simplex
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  ### Training Details
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- - **Training Session**: 20251007_215344
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- - **Best Accuracy**: 0.5161
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- - **Epochs Trained**: 41
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  - **Batch Size**: 512
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  - **Learning Rate**: 0.0001
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  - **Adaptive Augmentation**: Enabled
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  ### Loss Configuration
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- - Task Loss Weight: 0.5
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- - Flow Alignment Weight: 0.5
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- - Coherence Weight: 0.3
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- - Multi-Scale Weight: 0.2
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  ### TensorBoard Logs
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  Training logs are available in the repository at:
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  ```
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- logs/beatrix-cifar100/20251007_215344
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  ```
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  To view them locally:
@@ -88,7 +89,7 @@ To view them locally:
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  git clone https://huggingface.co/AbstractPhil/vit-beatrix
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  # View logs in TensorBoard
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- tensorboard --logdir vit-beatrix/logs/beatrix-cifar100/20251007_215344
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  ```
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  ## Usage
@@ -133,18 +134,18 @@ with open(manifest_path, 'r') as f:
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  for key, info in sorted(manifest.items(), key=lambda x: x[1]['accuracy'], reverse=True):
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  print(f"{info['model_name']} ({info['timestamp']}): {info['accuracy']:.4f}")
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- # Download weights for the latest training session of beatrix-cifar100
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  weights_path = hf_hub_download(
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  repo_id="AbstractPhil/vit-beatrix",
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- filename="weights/beatrix-cifar100/20251007_215344/model.safetensors"
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  )
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  # Load model
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  model = SimplifiedGeometricClassifier(
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  num_classes=100,
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  img_size=32,
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- embed_dim=512,
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- depth=12
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  )
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  # Load weights
 
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  | beatrix-cifar100 | 20251007_195812 | 0.4701 | 42 | `weights/beatrix-cifar100/20251007_195812` | `logs/beatrix-cifar100/20251007_195812` |
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  | beatrix-cifar100 | 20251007_203741 | 0.4324 | 40 | `weights/beatrix-cifar100/20251007_203741` | `logs/beatrix-cifar100/20251007_203741` |
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  | beatrix-cifar100 | 20251007_193112 | 0.2802 | 10 | `weights/beatrix-cifar100/20251007_193112` | `N/A` |
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+ | beatrix-4simplex-45d | 20251007_231008 | 0.0546 | 0 | `weights/beatrix-4simplex-45d/20251007_231008` | `logs/beatrix-4simplex-45d/20251007_231008` |
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+ ## Latest Updated Model: beatrix-4simplex-45d (Session: 20251007_231008)
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  ### Model Details
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  - **Architecture**: Vision Transformer with fractal positional encoding
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  - **Dataset**: CIFAR-100 (100 classes)
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+ - **Embedding Dimension**: 45
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+ - **Depth**: 22 layers
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  - **Patch Size**: 4x4
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  - **PE Levels**: 12
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+ - **Simplex Dimension**: 4-simplex
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  ### Training Details
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+ - **Training Session**: 20251007_231008
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+ - **Best Accuracy**: 0.0546
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+ - **Epochs Trained**: 0
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  - **Batch Size**: 512
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  - **Learning Rate**: 0.0001
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  - **Adaptive Augmentation**: Enabled
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  ### Loss Configuration
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+ - Task Loss Weight: 1.0
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+ - Flow Alignment Weight: 0.4
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+ - Coherence Weight: 0.2
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+ - Multi-Scale Weight: 0.1
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  ### TensorBoard Logs
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  Training logs are available in the repository at:
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  ```
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+ logs/beatrix-4simplex-45d/20251007_231008
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  ```
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  To view them locally:
 
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  git clone https://huggingface.co/AbstractPhil/vit-beatrix
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  # View logs in TensorBoard
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+ tensorboard --logdir vit-beatrix/logs/beatrix-4simplex-45d/20251007_231008
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  ```
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  ## Usage
 
134
  for key, info in sorted(manifest.items(), key=lambda x: x[1]['accuracy'], reverse=True):
135
  print(f"{info['model_name']} ({info['timestamp']}): {info['accuracy']:.4f}")
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+ # Download weights for the latest training session of beatrix-4simplex-45d
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  weights_path = hf_hub_download(
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  repo_id="AbstractPhil/vit-beatrix",
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+ filename="weights/beatrix-4simplex-45d/20251007_231008/model.safetensors"
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  )
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  # Load model
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  model = SimplifiedGeometricClassifier(
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  num_classes=100,
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  img_size=32,
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+ embed_dim=45,
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+ depth=22
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  )
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  # Load weights
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manifest.json CHANGED
@@ -55,5 +55,17 @@
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  "depth": 12,
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  "batch_size": 512,
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  "learning_rate": 0.0001
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  }
 
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  "depth": 12,
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  "batch_size": 512,
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  "learning_rate": 0.0001
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+ },
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+ "beatrix-4simplex-45d_20251007_231008": {
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+ "accuracy": 0.054647288657724856,
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+ "epoch": 0,
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+ "timestamp": "20251007_231008",
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+ "model_name": "beatrix-4simplex-45d",
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+ "path": "weights/beatrix-4simplex-45d/20251007_231008",
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+ "logs_path": "logs/beatrix-4simplex-45d/20251007_231008",
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+ "embed_dim": 45,
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+ "depth": 22,
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+ "batch_size": 512,
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+ "learning_rate": 0.0001
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  }
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  }
weights/beatrix-4simplex-45d/20251007_231008/config.json ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "num_classes": 100,
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+ "img_size": 32,
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+ "patch_size": 4,
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+ "embed_dim": 45,
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+ "k_simplex": 4,
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+ "depth": 22,
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+ "num_heads": 5,
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+ "mlp_ratio": 4.0,
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+ "dropout": 0.0,
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+ "pe_levels": 12,
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+ "pe_features_per_level": 2,
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+ "pe_smooth_tau": 0.25,
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+ "batch_size": 512,
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+ "num_epochs": 100,
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+ "learning_rate": 0.0001,
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+ "weight_decay": 0.005,
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+ "warmup_epochs": 0,
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+ "task_loss_weight": 1.0,
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+ "flow_loss_weight": 0.4,
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+ "use_adaptive_augmentation": true,
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+ "overfit_threshold": 0.02,
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+ "mixup_alpha": 0.2,
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+ "cutmix_alpha": 1.0,
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+ "device": "cuda",
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+ "num_workers": 4,
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+ "pin_memory": true,
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+ "save_dir": "./checkpoints",
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+ "save_every": 10,
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+ "hub_model_name": "beatrix-4simplex-45d",
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+ "hub_upload_best_only": true,
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+ "hub_upload_every_n_epochs": 10,
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+ "use_tensorboard": true,
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+ "log_dir": "./logs",
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+ "log_every": 50,
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+ "train_baseline": false
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+ }
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