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{
"model_type": "adaptive_repetition_controller",
"version": "1.0.0",
"architecture": {
"d_model": 4096,
"n_layers": 32,
"d_fiber": 16,
"d_control": 64,
"rep_window": 32,
"total_params": 50000
},
"training": {
"dataset": "wikitext-2",
"loss": "BCEWithLogitsLoss",
"pos_weight": "dynamic",
"lr_predictor": 1e-4,
"lr_lora": 2e-5,
"batch_size": 4,
"gradient_accumulation": 8,
"optimal_steps": 5000
},
"performance": {
"f1_score": 0.99,
"risk_at_repeats": 0.998,
"risk_at_non_repeats": 0.008,
"separation": "125x",
"repetition_reduction": "48.4%",
"distinct2_improvement": "16.7%"
},
"inference": {
"penalty_scale_default": 3.0,
"temperature_default": 0.8,
"threshold_default": 0.1,
"rep_window": 32
},
"base_model_compatibility": [
"llama-3.1-8b",
"llama-3-8b",
"mistral-7b"
],
"notes": "This is a decode-time intervention system, not an attention modification. The geometric CF-HoT theory remains unvalidated; this is the working practical implementation."
}
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