horizon-v1 / config.json
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{
"model_type": "horizon_causal_dit",
"version": "1.0.0",
"architecture": {
"type": "ConditionalDiT1D",
"d_model": 768,
"n_blocks": 16,
"n_heads": 12,
"d_in": 5,
"T": 63,
"dropout": 0.0,
"mlp_ratio": 4.0,
"d_c_vec_raw": 17,
"n_event_types": 8,
"L_max": 8,
"d_nl": 384,
"nl_bottleneck_dim": 256,
"n_nl_tokens": 4,
"total_params": 172376579
},
"training": {
"steps": 200000,
"batch_size": 128,
"grad_accumulation": 2,
"effective_batch": 256,
"learning_rate": 3e-4,
"warmup_steps": 5000,
"optimizer": "AdamW",
"weight_decay": 0.01,
"precision": "bf16",
"sigma_data": 0.9904,
"final_loss": 0.06
},
"data": {
"n_symbols": 50,
"n_headlines": 1054286,
"n_macro_series": 48,
"n_training_windows": 317650,
"window_size": 63,
"date_range": "2000-01-04 to 2026-05-04"
},
"causal": {
"graph_nodes": 14,
"graph_edges": 18,
"guidance_scale_default": 2.0,
"inversion_steps": 100,
"sampling_steps": 15,
"sigma_max": 2.0,
"calibrated": true
},
"benchmark": {
"world_properties": "5/5 PASS",
"causal_validity": "3/3 PASS",
"natural_experiments": "42/42 RBI events direction match",
"calibration_error_rate_cut": "2.4%",
"counterfactual_coherence": 0.975,
"pearl_level": 3
}
}