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config.py

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+from dataclasses import dataclass
+
+
+@dataclass
+class TrainingConfig:
+    """Configuration for training (as a dataclass)."""
+
+    # Model parameters
+    d_model: int = 512
+    n_heads: int = 8
+    n_encoder_layers: int = 6
+    n_decoder_layers: int = 6
+    vocab_in: int = 12  # digits 0-9 + padding token + start
+    vocab_out: int = 11  # digits 0-9 + padding token + start
+    block_size_in: int = 128  # max length of position n
+    block_size_out: int = 129  # context_length + 1 (inclusive)
+    pad_token: int = -1
+    start_token: int = 10
+
+    # Training parameters
+    batch_size: int = 64
+    learning_rate: float = 1e-4
+    weight_decay: float = 0.01
+    num_epochs: int = 100
+    gradient_clip: float = 1.0
+    warmup_steps: int = 1000
+
+    # Dataset parameters
+    context_length: int = 128
+    train_split: float = 0.9
+    num_workers: int = 4
+    device: str = "cpu"
+
+    # Logging and checkpointing
+    log_interval: int = 100
+    eval_interval: int = 1000
+    save_interval: int = 5000
+    checkpoint_dir: str = "checkpoints"
+    log_dir: str = "runs"