Export trained reference models

README.md

@@ -12,9 +12,9 @@ Unconditional reference models trained with gendynamics. The weights correspond
 
 ## Dataset
 
-USDA Forest Service FPA-FOD current-edition fire occurrences. [Upstream source](https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query). Sample distinct 1992–2024 records with positive final fire size, retain size in acres, and randomly split 10,000/1,000/1,000,000 records. Columns: fire_size. 
-The train/validation/test splits contain 10,000/1,000/1,000,000 samples
-of shape `[1]`. Normalization: Per-coordinate training mean and standard deviation; zero deviations replaced by one. The processed dataset file `us_wildfire_size.pt` has SHA-256 `3eada73c9713a1d8e55c32aa7d8779095c80cfbaaab50b0b9ca764bc72714596`. 
+USDA Forest Service FPA-FOD current-edition fire occurrences. [Upstream source](https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query). Sample distinct 1992–2024 records with positive final fire size, retain size in acres, and randomly split 25,000/1,000/1,000,000 records. Columns: fire_size. 
+The train/validation/test splits contain 25,000/1,000/1,000,000 samples
+of shape `[1]`. Normalization: Per-coordinate training mean and standard deviation; zero deviations replaced by one. The processed dataset file `us_wildfire_size.pt` has SHA-256 `956da0a080086dcf598ec633a292e619856bbb6389d0548e092f7248087a9e19`. 
 The exact generator arguments or processed-file identity, split settings, and seed are in `dataset.json`.
 The source data themselves are not redistributed here; source-data terms remain with their provider.
 The preparation code is in `datasets/3_us_wildfire_size_dataset.py` in the [training repository](https://github.com/Diffusion-Research-Lab/2_training_2026_tail_reference_models). API-backed sources can change; the processed-file checksum identifies this snapshot.
@@ -39,9 +39,9 @@ All independently trained models use this network architecture:
 
 | Directory | Model | Prediction target | Trainable parameters | Sampling steps | Learning rate | Epochs run / best | Val loss | Test loss |
 |---|---|---|---:|---:|---:|---:|---:|---:|
-| ddpm-v | DDPM-V | velocity | 133,505 | 128 | 0.0005 | 320 / 220 | 0.06737 | 0.3116 |
-| dlpm-eps | DLPM-Eps | noise | 133,505 | 128 | 0.0005 | 325 / 225 | 0.03906 | 0.06159 |
-| tedm-origin | t-EDM | denoised data | 133,505 | 64 | 0.0005 | 218 / 118 | 0.09057 | 0.4965 |
+| ddpm-v | DDPM-V | velocity | 133,505 | 128 | 0.0005 | 374 / 274 | 0.09306 | 0.0727 |
+| dlpm-eps | DLPM-Eps | noise | 133,505 | 128 | 0.0005 | 549 / 449 | 0.01579 | 0.03829 |
+| tedm-origin | t-EDM | denoised data | 133,505 | 64 | 0.0005 | 191 / 91 | 0.1577 | 0.1586 |
 
 The complete **selected final** model and training settings are below and in each directory's `config.json`.
 The training settings include the maximum epoch budget; `epochs run / best` reports what actually happened.
@@ -86,7 +86,7 @@ The number of held-out rows used for each test loss is in `metrics.json`. Sample
 {
   "model_parameters": {
     "n_steps": 128,
-    "alpha": 1.9,
+    "alpha": 1.8,
     "sampler": "native"
   },
   "training": {
@@ -117,7 +117,7 @@ The number of held-out rows used for each test loss is in `metrics.json`. Sample
 {
   "model_parameters": {
     "n_steps": 64,
-    "nu": 3.0,
+    "nu": 2.2,
     "sigma_min": 0.005,
     "sigma_max": 5.0,
     "sigma_data": 1.0,

ddim-v/config.json

@@ -34,14 +34,14 @@
       "dlpm_eps": {
         "params": {
           "n_steps": 128,
-          "alpha": 1.7,
+          "alpha": 1.8,
           "sampler": "native"
         }
       },
       "tedm_origin": {
         "params": {
           "n_steps": 64,
-          "nu": 2.1,
+          "nu": 2.2,
           "sigma_min": 0.005,
           "sigma_max": 5.0,
           "sigma_data": 1.0,
@@ -73,12 +73,6 @@
           }
         },
         "dlpm_eps": {
-          "model": {
-            "alpha": [
-              1.7,
-              1.9
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -87,12 +81,6 @@
           }
         },
         "tedm_origin": {
-          "model": {
-            "nu": [
-              2.1,
-              3.0
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -144,5 +132,5 @@
   "sample_shape": [
     1
   ],
-  "data_scale": 0.05718296766281128
+  "data_scale": 0.03256954997777939
 }

ddim-v/dataset.json

@@ -7,11 +7,11 @@
   },
   "split_mode": "predefined",
   "counts": {
-    "train": 10000,
+    "train": 25000,
     "validation": 1000,
     "test": 1000000
   },
-  "n_samples": 1011000,
+  "n_samples": 1026000,
   "sample_shape": [
     1
   ],
@@ -19,7 +19,7 @@
   "normalization": "Per-coordinate training mean and standard deviation; zero deviations replaced by one.",
   "source": {
     "filename": "us_wildfire_size.pt",
-    "sha256": "3eada73c9713a1d8e55c32aa7d8779095c80cfbaaab50b0b9ca764bc72714596",
+    "sha256": "956da0a080086dcf598ec633a292e619856bbb6389d0548e092f7248087a9e19",
     "url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "columns": [
       "fire_size"
@@ -31,6 +31,6 @@
     "origin": "USDA Forest Service FPA-FOD current-edition fire occurrences",
     "source_url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "preparation_script": "datasets/3_us_wildfire_size_dataset.py",
-    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 10,000/1,000/1,000,000 records."
+    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 25,000/1,000/1,000,000 records."
   }
 }

ddim-v/export_check.json

@@ -10,9 +10,9 @@
   "device": "cpu",
   "model_dtype": "torch.float32",
   "sample_dtype": "torch.float32",
-  "min": -5.4490509033203125,
-  "max": 3.755462646484375,
-  "std": 3.8903496537508713,
+  "min": -17.79375457763672,
+  "max": 6.156951904296875,
+  "std": 10.353967080330325,
   "clamp_min": null,
   "clipped_fraction": 0.0,
   "scope": "Shape and numerical validity only; not distribution quality or tail accuracy.",

ddim-v/metrics.json

@@ -1,6 +1,6 @@
 {
-  "best_epoch": 220,
-  "validation_loss": 0.06736978301405906,
+  "best_epoch": 274,
+  "validation_loss": 0.09306336095929146,
   "test_loss_samples": 2000,
-  "test_loss": 0.3116239735484123
+  "test_loss": 0.0727011608183384
 }

ddim-v/model.safetensors

@@ -1,3 +1,3 @@
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ddim-v/normalization.safetensors

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ddim-v/provenance.json

@@ -1,5 +1,5 @@
 {
-  "recorded_at_utc": "2026-10-04T00:19:17.497598+00:00",
+  "recorded_at_utc": "2026-10-04T04:42:39.651698+00:00",
   "python": "3.12.11",
   "platform": "Linux-5.14.0-570.131.1.el9_6.x86_64-x86_64-with-glibc2.34",
   "device": "cuda",

ddpm-v/config.json

@@ -34,14 +34,14 @@
       "dlpm_eps": {
         "params": {
           "n_steps": 128,
-          "alpha": 1.7,
+          "alpha": 1.8,
           "sampler": "native"
         }
       },
       "tedm_origin": {
         "params": {
           "n_steps": 64,
-          "nu": 2.1,
+          "nu": 2.2,
           "sigma_min": 0.005,
           "sigma_max": 5.0,
           "sigma_data": 1.0,
@@ -73,12 +73,6 @@
           }
         },
         "dlpm_eps": {
-          "model": {
-            "alpha": [
-              1.7,
-              1.9
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -87,12 +81,6 @@
           }
         },
         "tedm_origin": {
-          "model": {
-            "nu": [
-              2.1,
-              3.0
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -142,5 +130,5 @@
   "sample_shape": [
     1
   ],
-  "data_scale": 0.05718296766281128
+  "data_scale": 0.03256954997777939
 }

ddpm-v/dataset.json

@@ -7,11 +7,11 @@
   },
   "split_mode": "predefined",
   "counts": {
-    "train": 10000,
+    "train": 25000,
     "validation": 1000,
     "test": 1000000
   },
-  "n_samples": 1011000,
+  "n_samples": 1026000,
   "sample_shape": [
     1
   ],
@@ -19,7 +19,7 @@
   "normalization": "Per-coordinate training mean and standard deviation; zero deviations replaced by one.",
   "source": {
     "filename": "us_wildfire_size.pt",
-    "sha256": "3eada73c9713a1d8e55c32aa7d8779095c80cfbaaab50b0b9ca764bc72714596",
+    "sha256": "956da0a080086dcf598ec633a292e619856bbb6389d0548e092f7248087a9e19",
     "url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "columns": [
       "fire_size"
@@ -31,6 +31,6 @@
     "origin": "USDA Forest Service FPA-FOD current-edition fire occurrences",
     "source_url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "preparation_script": "datasets/3_us_wildfire_size_dataset.py",
-    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 10,000/1,000/1,000,000 records."
+    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 25,000/1,000/1,000,000 records."
   }
 }

ddpm-v/export_check.json

@@ -10,9 +10,9 @@
   "device": "cpu",
   "model_dtype": "torch.float32",
   "sample_dtype": "torch.float32",
-  "min": 2.0190811157226562,
-  "max": 3.616973876953125,
-  "std": 0.5797488799655913,
+  "min": 6.036949157714844,
+  "max": 9.384300231933594,
+  "std": 1.4120274784027709,
   "clamp_min": null,
   "clipped_fraction": 0.0,
   "scope": "Shape and numerical validity only; not distribution quality or tail accuracy.",

ddpm-v/metrics.json

@@ -1,6 +1,6 @@
 {
-  "best_epoch": 220,
-  "validation_loss": 0.06736978301405906,
+  "best_epoch": 274,
+  "validation_loss": 0.09306336095929146,
   "test_loss_samples": 2000,
-  "test_loss": 0.3116239735484123
+  "test_loss": 0.0727011608183384
 }

ddpm-v/model.safetensors

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ddpm-v/normalization.safetensors

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ddpm-v/provenance.json

@@ -1,5 +1,5 @@
 {
-  "recorded_at_utc": "2026-10-04T00:19:17.497598+00:00",
+  "recorded_at_utc": "2026-10-04T04:42:39.651698+00:00",
   "python": "3.12.11",
   "platform": "Linux-5.14.0-570.131.1.el9_6.x86_64-x86_64-with-glibc2.34",
   "device": "cuda",

dlpm-eps/config.json

@@ -34,14 +34,14 @@
       "dlpm_eps": {
         "params": {
           "n_steps": 128,
-          "alpha": 1.9,
+          "alpha": 1.8,
           "sampler": "native"
         }
       },
       "tedm_origin": {
         "params": {
           "n_steps": 64,
-          "nu": 2.1,
+          "nu": 2.2,
           "sigma_min": 0.005,
           "sigma_max": 5.0,
           "sigma_data": 1.0,
@@ -73,12 +73,6 @@
           }
         },
         "dlpm_eps": {
-          "model": {
-            "alpha": [
-              1.7,
-              1.9
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -87,12 +81,6 @@
           }
         },
         "tedm_origin": {
-          "model": {
-            "nu": [
-              2.1,
-              3.0
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -136,11 +124,11 @@
   "model_name": "dlpm_eps",
   "model_params": {
     "n_steps": 128,
-    "alpha": 1.9,
+    "alpha": 1.8,
     "sampler": "native"
   },
   "sample_shape": [
     1
   ],
-  "data_scale": 0.05718296766281128
+  "data_scale": 0.03256954997777939
 }

dlpm-eps/dataset.json

@@ -7,11 +7,11 @@
   },
   "split_mode": "predefined",
   "counts": {
-    "train": 10000,
+    "train": 25000,
     "validation": 1000,
     "test": 1000000
   },
-  "n_samples": 1011000,
+  "n_samples": 1026000,
   "sample_shape": [
     1
   ],
@@ -19,7 +19,7 @@
   "normalization": "Per-coordinate training mean and standard deviation; zero deviations replaced by one.",
   "source": {
     "filename": "us_wildfire_size.pt",
-    "sha256": "3eada73c9713a1d8e55c32aa7d8779095c80cfbaaab50b0b9ca764bc72714596",
+    "sha256": "956da0a080086dcf598ec633a292e619856bbb6389d0548e092f7248087a9e19",
     "url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "columns": [
       "fire_size"
@@ -31,6 +31,6 @@
     "origin": "USDA Forest Service FPA-FOD current-edition fire occurrences",
     "source_url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "preparation_script": "datasets/3_us_wildfire_size_dataset.py",
-    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 10,000/1,000/1,000,000 records."
+    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 25,000/1,000/1,000,000 records."
   }
 }

dlpm-eps/export_check.json

@@ -10,9 +10,9 @@
   "device": "cpu",
   "model_dtype": "torch.float32",
   "sample_dtype": "torch.float32",
-  "min": 3.5623435974121094,
-  "max": 4.478218078613281,
-  "std": 0.3449531695953566,
+  "min": -0.20629119873046875,
+  "max": 2.6162643432617188,
+  "std": 1.1660823631509063,
   "clamp_min": null,
   "clipped_fraction": 0.0,
   "scope": "Shape and numerical validity only; not distribution quality or tail accuracy.",

dlpm-eps/metrics.json

@@ -1,6 +1,6 @@
 {
-  "best_epoch": 225,
-  "validation_loss": 0.03906210622191429,
+  "best_epoch": 449,
+  "validation_loss": 0.015788927465677262,
   "test_loss_samples": 2000,
-  "test_loss": 0.06158529408276081
+  "test_loss": 0.03829278013110161
 }

dlpm-eps/model.safetensors

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dlpm-eps/normalization.safetensors

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dlpm-eps/provenance.json

@@ -1,5 +1,5 @@
 {
-  "recorded_at_utc": "2026-10-04T00:19:17.497877+00:00",
+  "recorded_at_utc": "2026-10-04T04:41:38.251129+00:00",
   "python": "3.12.11",
   "platform": "Linux-5.14.0-570.131.1.el9_6.x86_64-x86_64-with-glibc2.34",
   "device": "cuda",

tedm-origin/config.json

@@ -34,14 +34,14 @@
       "dlpm_eps": {
         "params": {
           "n_steps": 128,
-          "alpha": 1.7,
+          "alpha": 1.8,
           "sampler": "native"
         }
       },
       "tedm_origin": {
         "params": {
           "n_steps": 64,
-          "nu": 3.0,
+          "nu": 2.2,
           "sigma_min": 0.005,
           "sigma_max": 5.0,
           "sigma_data": 1.0,
@@ -73,12 +73,6 @@
           }
         },
         "dlpm_eps": {
-          "model": {
-            "alpha": [
-              1.7,
-              1.9
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -87,12 +81,6 @@
           }
         },
         "tedm_origin": {
-          "model": {
-            "nu": [
-              2.1,
-              3.0
-            ]
-          },
           "train": {
             "lr": [
               0.0002,
@@ -136,7 +124,7 @@
   "model_name": "tedm_origin",
   "model_params": {
     "n_steps": 64,
-    "nu": 3.0,
+    "nu": 2.2,
     "sigma_min": 0.005,
     "sigma_max": 5.0,
     "sigma_data": 1.0,
@@ -145,5 +133,5 @@
   "sample_shape": [
     1
   ],
-  "data_scale": 0.05718296766281128
+  "data_scale": 0.03256954997777939
 }

tedm-origin/dataset.json

@@ -7,11 +7,11 @@
   },
   "split_mode": "predefined",
   "counts": {
-    "train": 10000,
+    "train": 25000,
     "validation": 1000,
     "test": 1000000
   },
-  "n_samples": 1011000,
+  "n_samples": 1026000,
   "sample_shape": [
     1
   ],
@@ -19,7 +19,7 @@
   "normalization": "Per-coordinate training mean and standard deviation; zero deviations replaced by one.",
   "source": {
     "filename": "us_wildfire_size.pt",
-    "sha256": "3eada73c9713a1d8e55c32aa7d8779095c80cfbaaab50b0b9ca764bc72714596",
+    "sha256": "956da0a080086dcf598ec633a292e619856bbb6389d0548e092f7248087a9e19",
     "url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "columns": [
       "fire_size"
@@ -31,6 +31,6 @@
     "origin": "USDA Forest Service FPA-FOD current-edition fire occurrences",
     "source_url": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceCurrentEdition_01/MapServer/0/query",
     "preparation_script": "datasets/3_us_wildfire_size_dataset.py",
-    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 10,000/1,000/1,000,000 records."
+    "preparation": "Sample distinct 1992\u20132024 records with positive final fire size, retain size in acres, and randomly split 25,000/1,000/1,000,000 records."
   }
 }

tedm-origin/export_check.json

@@ -10,9 +10,9 @@
   "device": "cpu",
   "model_dtype": "torch.float32",
   "sample_dtype": "torch.float32",
-  "min": -13.515121459960938,
-  "max": 1.7646141052246094,
-  "std": 5.427535032386916,
+  "min": -63.533935546875,
+  "max": 18.137989044189453,
+  "std": 29.715100703203557,
   "clamp_min": null,
   "clipped_fraction": 0.0,
   "scope": "Shape and numerical validity only; not distribution quality or tail accuracy.",

tedm-origin/metrics.json

@@ -1,6 +1,6 @@
 {
-  "best_epoch": 118,
-  "validation_loss": 0.09057306885719299,
+  "best_epoch": 91,
+  "validation_loss": 0.157678666472435,
   "test_loss_samples": 2000,
-  "test_loss": 0.49652962589263916
+  "test_loss": 0.15862367516756057
 }

tedm-origin/model.safetensors

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tedm-origin/normalization.safetensors

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tedm-origin/provenance.json

@@ -1,9 +1,9 @@
 {
-  "recorded_at_utc": "2026-10-04T00:19:48.447439+00:00",
+  "recorded_at_utc": "2026-10-04T04:41:48.770883+00:00",
   "python": "3.12.11",
   "platform": "Linux-5.14.0-570.131.1.el9_6.x86_64-x86_64-with-glibc2.34",
   "device": "cuda",
-  "gpu": "Tesla V100-SXM2-16GB",
+  "gpu": "Tesla V100-SXM2-32GB",
   "cuda_version": "12.8",
   "source": {
     "commit": null,