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README.md

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-license: mit
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+# Deepfake Detector V10
+
+## Improvements over V9
+- 20% more data (12K samples vs 10K)
+- 10 NEW fake types (completely different patterns)
+- 5 epochs vs 3 (66% more training)
+- Lower LR (5e-5) for better fine-tuning
+- Stronger augmentation
+- All layers unfrozen (full learning)
+
+## Performance
+- V9: 99.95%
+- V10: 100.00%
+- Improvement: +0.05%
+- F1: 1.0000
+
+## Files
+All retraining files included. Ready for HuggingFace.

config.json

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+{"architecture": "tf_efficientnetv2_s", "dropout": 0.55}

metrics.json

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+{"version": "V10", "best_accuracy": 1.0, "best_f1": 1.0, "train_samples": 9600, "val_samples": 2400, "v9_baseline": 0.9995}

model.safetensors

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+size 84569652

optimizer.pt

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+size 168118663

rng_state.pth

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+size 14391

scheduler.pt

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+size 1465

tokenizer.json

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+{"version": "V10", "type": "image"}

tokenizer_config.json

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+{"model_type": "image_classification", "version": "V10"}

training_args.json

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+{"target_real": 6000, "target_fake": 6000, "val_split": 0.2, "epochs": 5, "batch_size": 24, "learning_rate": 5e-05, "weight_decay": 0.0002, "dropout": 0.55, "label_smoothing": 0.2, "save_dir": "./deepfake_v10_model"}