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base_config.yaml

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+# Configuration: base_config.yaml
+#
+# Global training parameters. Consumed by training/train_semantic.py,
+# training/train_frequency.py, and training/data/{dataset,datamodule}.py.
+
+seed: 42
+image_size: 512
+batch_size: 16
+num_workers: 0
+lr: 0.0001
+
+# Stream-specific settings.
+semantic:
+  pretrained: true
+  freeze_backbone: true
+  unfreeze_last_n_blocks: 2
+  output_dim: 1024
+
+frequency:
+  pretrained: true
+  freeze_backbone: false
+  highpass_ratio: 0.08
+  output_dim: 768
+
+data:
+  # Path to a manifest CSV with an `image_path,label` header (0=Real, 1=AI-Generated).
+  # Falls back to an in-memory synthetic dataset for pipeline testing if this
+  # path doesn't exist yet. Produced by (see training/data/import_hf.py and
+  # training/data/shuffle_manifest.py):
+  #   python -m training.data.import_hf --split train --output data/sid_subset --limit <N>
+  #   python -m training.data.shuffle_manifest --input data/sid_subset/manifest.csv --output data/sid_subset/manifest_shuffled.csv
+  manifest_path: data/sid_binary_10000/manifest.csv
+  num_synthetic_samples: 32
+  val_split: 0.2
+
+log_level: INFO