trinetra-data / models /train_report.json
aryapatil's picture
Upload folder using huggingface_hub
840020c verified
Raw History Blame Contribute Delete
17.3 kB
{
"config": {
"epochs": 16,
"size": 96,
"seq": 6,
"batch": 24,
"lr": 0.002,
"weight_decay": 0.0001,
"max_storms": 90,
"holdout_seasons": 4,
"threads": 8,
"seed": 0,
"out": "/Users/arya/Documents/College/projects/trinetra/data/models/trinetra.pt"
},
"model_version": "trinetra-0.4.1",
"parameters": 585485,
"split": {
"protocol": "chronological holdout",
"test_seasons": [
2021,
2022,
2023,
2024
],
"train_fixes": 4890,
"test_fixes": 797,
"group_key": "sid"
},
"provenance_warning": "The image channels are generated by this project's own forward model. The analysis metrics below therefore measure how well the network inverts that forward model and validate the pipeline. They are not a claim about satellite intensity estimation. The forecast table, which runs on real best-track predictors, is.",
"history": [
{
"epoch": 1,
"seconds": 262.7,
"train_loss": 3.2294,
"test_vmax_rmse": 16.697,
"test_centre_median_km": 60.01,
"test_category_macro_f1": 0.0918,
"test_ri_auc": 0.6233,
"losses": {
"vmax": 0.1906,
"pmin": 0.2087,
"category": 0.5514,
"detection": 0.2796,
"dvorak": 0.9707,
"regime": 0.5778,
"ri": 0.3215,
"reintensify": 0.108,
"centre": 1.5646
}
},
{
"epoch": 2,
"seconds": 264.7,
"train_loss": 1.2147,
"test_vmax_rmse": 5.758,
"test_centre_median_km": 68.23,
"test_category_macro_f1": 0.3888,
"test_ri_auc": 0.7957,
"losses": {
"vmax": -0.8606,
"pmin": -0.6238,
"category": 0.3345,
"detection": 0.2286,
"dvorak": 0.5528,
"regime": 0.346,
"ri": 0.3007,
"reintensify": 0.0724,
"centre": 1.3475
}
},
{
"epoch": 3,
"seconds": 426.7,
"train_loss": 1.0282,
"test_vmax_rmse": 6.307,
"test_centre_median_km": 73.84,
"test_category_macro_f1": 0.5431,
"test_ri_auc": 0.7981,
"losses": {
"vmax": -0.8114,
"pmin": -0.6508,
"category": 0.2163,
"detection": 0.2256,
"dvorak": 0.3842,
"regime": 0.2809,
"ri": 0.2921,
"reintensify": 0.0492,
"centre": 1.285
}
},
{
"epoch": 4,
"seconds": 277.5,
"train_loss": 0.9945,
"test_vmax_rmse": 19.661,
"test_centre_median_km": 70.33,
"test_category_macro_f1": 0.1396,
"test_ri_auc": 0.7394,
"losses": {
"vmax": -0.7807,
"pmin": -0.6285,
"category": 0.1833,
"detection": 0.2203,
"dvorak": 0.3431,
"regime": 0.2428,
"ri": 0.2938,
"reintensify": 0.054,
"centre": 1.2639
}
},
{
"epoch": 5,
"seconds": 277.3,
"train_loss": 0.8001,
"test_vmax_rmse": 8.315,
"test_centre_median_km": 74.06,
"test_category_macro_f1": 0.4909,
"test_ri_auc": 0.8132,
"losses": {
"vmax": -0.9105,
"pmin": -0.6826,
"category": 0.1695,
"detection": 0.2017,
"dvorak": 0.2996,
"regime": 0.22,
"ri": 0.2969,
"reintensify": 0.04,
"centre": 1.2583
}
},
{
"epoch": 6,
"seconds": 269.1,
"train_loss": 0.2793,
"test_vmax_rmse": 11.835,
"test_centre_median_km": 74.65,
"test_category_macro_f1": 0.5106,
"test_ri_auc": 0.8122,
"losses": {
"vmax": -1.2552,
"pmin": -0.8972,
"category": 0.1114,
"detection": 0.1939,
"dvorak": 0.2371,
"regime": 0.2031,
"ri": 0.2811,
"reintensify": 0.0342,
"centre": 1.2431
}
},
{
"epoch": 7,
"seconds": 312.3,
"train_loss": 0.0991,
"test_vmax_rmse": 5.952,
"test_centre_median_km": 75.27,
"test_category_macro_f1": 0.7046,
"test_ri_auc": 0.8498,
"losses": {
"vmax": -1.3524,
"pmin": -0.9729,
"category": 0.0952,
"detection": 0.1791,
"dvorak": 0.2016,
"regime": 0.1783,
"ri": 0.2731,
"reintensify": 0.0335,
"centre": 1.234
}
},
{
"epoch": 8,
"seconds": 316.4,
"train_loss": -0.3797,
"test_vmax_rmse": 3.704,
"test_centre_median_km": 75.2,
"test_category_macro_f1": 0.8097,
"test_ri_auc": 0.8469,
"losses": {
"vmax": -1.7193,
"pmin": -1.122,
"category": 0.0658,
"detection": 0.1729,
"dvorak": 0.1571,
"regime": 0.1674,
"ri": 0.2571,
"reintensify": 0.0233,
"centre": 1.2318
}
},
{
"epoch": 9,
"seconds": 331.4,
"train_loss": -0.3634,
"test_vmax_rmse": 2.869,
"test_centre_median_km": 74.92,
"test_category_macro_f1": 0.8731,
"test_ri_auc": 0.878,
"losses": {
"vmax": -1.6792,
"pmin": -1.1403,
"category": 0.0664,
"detection": 0.1669,
"dvorak": 0.1599,
"regime": 0.1612,
"ri": 0.2523,
"reintensify": 0.0245,
"centre": 1.2242
}
},
{
"epoch": 10,
"seconds": 305.3,
"train_loss": -0.6989,
"test_vmax_rmse": 3.349,
"test_centre_median_km": 73.69,
"test_category_macro_f1": 0.8731,
"test_ri_auc": 0.8662,
"losses": {
"vmax": -1.963,
"pmin": -1.2298,
"category": 0.0518,
"detection": 0.1672,
"dvorak": 0.142,
"regime": 0.1535,
"ri": 0.2548,
"reintensify": 0.0212,
"centre": 1.2238
}
},
{
"epoch": 11,
"seconds": 294.6,
"train_loss": -0.8486,
"test_vmax_rmse": 2.194,
"test_centre_median_km": 74.97,
"test_category_macro_f1": 0.9045,
"test_ri_auc": 0.8972,
"losses": {
"vmax": -2.0644,
"pmin": -1.2628,
"category": 0.0444,
"detection": 0.1609,
"dvorak": 0.1319,
"regime": 0.1406,
"ri": 0.2398,
"reintensify": 0.0196,
"centre": 1.2177
}
},
{
"epoch": 12,
"seconds": 305.0,
"train_loss": -0.9565,
"test_vmax_rmse": 2.154,
"test_centre_median_km": 74.67,
"test_category_macro_f1": 0.9131,
"test_ri_auc": 0.8893,
"losses": {
"vmax": -2.1422,
"pmin": -1.2967,
"category": 0.0394,
"detection": 0.1567,
"dvorak": 0.1264,
"regime": 0.132,
"ri": 0.2346,
"reintensify": 0.0206,
"centre": 1.2158
}
},
{
"epoch": 13,
"seconds": 314.6,
"train_loss": -1.2226,
"test_vmax_rmse": 1.937,
"test_centre_median_km": 74.84,
"test_category_macro_f1": 0.9193,
"test_ri_auc": 0.8937,
"losses": {
"vmax": -2.3536,
"pmin": -1.3821,
"category": 0.0297,
"detection": 0.1565,
"dvorak": 0.1125,
"regime": 0.1268,
"ri": 0.2283,
"reintensify": 0.0187,
"centre": 1.2129
}
},
{
"epoch": 14,
"seconds": 271.5,
"train_loss": -1.2964,
"test_vmax_rmse": 1.782,
"test_centre_median_km": 74.56,
"test_category_macro_f1": 0.9379,
"test_ri_auc": 0.896,
"losses": {
"vmax": -2.4082,
"pmin": -1.3989,
"category": 0.0297,
"detection": 0.1553,
"dvorak": 0.111,
"regime": 0.1202,
"ri": 0.2223,
"reintensify": 0.015,
"centre": 1.2107
}
},
{
"epoch": 15,
"seconds": 265.4,
"train_loss": -1.4519,
"test_vmax_rmse": 1.501,
"test_centre_median_km": 74.06,
"test_category_macro_f1": 0.9441,
"test_ri_auc": 0.8895,
"losses": {
"vmax": -2.5346,
"pmin": -1.4497,
"category": 0.0227,
"detection": 0.1501,
"dvorak": 0.1032,
"regime": 0.1167,
"ri": 0.2234,
"reintensify": 0.0143,
"centre": 1.2106
}
},
{
"epoch": 16,
"seconds": 302.2,
"train_loss": -1.5266,
"test_vmax_rmse": 1.47,
"test_centre_median_km": 74.41,
"test_category_macro_f1": 0.9442,
"test_ri_auc": 0.8916,
"losses": {
"vmax": -2.5886,
"pmin": -1.4856,
"category": 0.0226,
"detection": 0.1509,
"dvorak": 0.1039,
"regime": 0.1157,
"ri": 0.218,
"reintensify": 0.0152,
"centre": 1.2089
}
}
],
"analysis": {
"vmax_rmse_ci": {
"point": 1.4703,
"ci_lo": 1.1621,
"ci_hi": 1.7115,
"level": 0.95
},
"vmax": {
"n": 797,
"rmse": 1.4703018038004185,
"mae": 0.871214654843511,
"bias": -0.17624831109902492,
"by_intensity": [
{
"bin": "17-33 kt (D, DD)",
"n": 409,
"rmse": 0.3575578925104322,
"mae": 0.289021517653337,
"bias": -0.07956730066126891
},
{
"bin": "34-47 kt (CS)",
"n": 133,
"rmse": 1.6602709756485998,
"mae": 0.9188454133227355,
"bias": 0.5693306313421493
},
{
"bin": "48-63 kt (SCS)",
"n": 109,
"rmse": 2.0554360057264405,
"mae": 1.6879181468158686,
"bias": -1.0440362352843677
},
{
"bin": "64-89 kt (VSCS)",
"n": 91,
"rmse": 2.1435155433505075,
"mae": 1.787029517875923,
"bias": 0.12531980577405993
},
{
"bin": "90+ kt (ESCS, SuCS)",
"n": 44,
"rmse": 3.0982592273875924,
"mae": 2.3312076221812856,
"bias": -1.9549532803622158
}
]
},
"centre_fix_km": {
"median": 74.41,
"p90": 131.55,
"mean": 76.69,
"first_guess_error_km": 70.0,
"note": "Residual after refining a deliberately offset first guess. The grid is storm-centred, so an unjittered target would be the middle of every sample and the head would score zero without learning anything."
},
"category": {
"n": 786,
"macro_f1": 0.9442467581129089,
"accuracy": 0.9516539440203562,
"confusion": [
[
236,
0,
0,
0,
0,
0,
0
],
[
11,
161,
1,
0,
0,
0,
0
],
[
0,
0,
122,
11,
0,
0,
0
],
[
0,
0,
5,
102,
2,
0,
0
],
[
0,
0,
0,
2,
84,
5,
0
],
[
0,
0,
0,
0,
1,
43,
0
],
[
0,
0,
0,
0,
0,
0,
0
]
],
"classes": [
"D",
"DD",
"CS",
"SCS",
"VSCS",
"ESCS",
"SuCS"
],
"per_class": [
{
"class": "D",
"support": 236,
"precision": 0.9555,
"recall": 1.0,
"f1": 0.9772
},
{
"class": "DD",
"support": 173,
"precision": 1.0,
"recall": 0.9306,
"f1": 0.9641
},
{
"class": "CS",
"support": 133,
"precision": 0.9531,
"recall": 0.9173,
"f1": 0.9349
},
{
"class": "SCS",
"support": 109,
"precision": 0.887,
"recall": 0.9358,
"f1": 0.9107
},
{
"class": "VSCS",
"support": 91,
"precision": 0.9655,
"recall": 0.9231,
"f1": 0.9438
},
{
"class": "ESCS",
"support": 44,
"precision": 0.8958,
"recall": 0.9773,
"f1": 0.9348
},
{
"class": "SuCS",
"support": 0,
"precision": 0.0,
"recall": 0.0,
"f1": 0.0
}
]
},
"regime": {
"n": 797,
"macro_f1": 0.7842036779457068,
"accuracy": 0.8569636135508155,
"confusion": [
[
252,
0,
10,
0
],
[
6,
226,
48,
0
],
[
7,
43,
30,
0
],
[
0,
0,
0,
175
]
],
"classes": [
"maritime_mature",
"sheared",
"post_landfall_remnant",
"over_land"
],
"per_class": [
{
"class": "maritime_mature",
"support": 262,
"precision": 0.9509,
"recall": 0.9618,
"f1": 0.9564
},
{
"class": "sheared",
"support": 280,
"precision": 0.8401,
"recall": 0.8071,
"f1": 0.8233
},
{
"class": "post_landfall_remnant",
"support": 80,
"precision": 0.3409,
"recall": 0.375,
"f1": 0.3571
},
{
"class": "over_land",
"support": 175,
"precision": 1.0,
"recall": 1.0,
"f1": 1.0
}
]
},
"conformal_vmax": {
"level": 0.9,
"half_width_kt": 2.51,
"empirical_coverage": 0.9021,
"by_intensity": {
"0-34": {
"quantile": 0.576,
"n": 420,
"coverage": 0.9024
},
"34-48": {
"quantile": 2.79,
"n": 133,
"coverage": 0.9098
},
"48-64": {
"quantile": 3.265,
"n": 109,
"coverage": 0.9083
},
"64-90": {
"quantile": 3.292,
"n": 91,
"coverage": 0.9121
},
"90-inf": {
"quantile": 5.9,
"n": 44,
"coverage": 0.9318
}
}
}
},
"ri_head": {
"n": 677,
"base_rate": 0.056129985228951254,
"mean_forecast": 0.04830054006273678,
"brier": 0.04270414029803309,
"brier_skill_score": 0.193948360157433,
"roc_auc": 0.8915657688822997,
"reliability": [
{
"bin_lo": 0.0,
"bin_hi": 0.1,
"n": 557,
"mean_forecast": 0.0168,
"observed_frequency": 0.0215
},
{
"bin_lo": 0.1,
"bin_hi": 0.2,
"n": 55,
"mean_forecast": 0.1419,
"observed_frequency": 0.0727
},
{
"bin_lo": 0.2,
"bin_hi": 0.3,
"n": 31,
"mean_forecast": 0.2414,
"observed_frequency": 0.1935
},
{
"bin_lo": 0.3,
"bin_hi": 0.4,
"n": 18,
"mean_forecast": 0.3425,
"observed_frequency": 0.4444
},
{
"bin_lo": 0.4,
"bin_hi": 0.5,
"n": 16,
"mean_forecast": 0.4477,
"observed_frequency": 0.5
}
],
"contingency": {
"threshold": 0.45,
"hits": 4,
"misses": 34,
"false_alarms": 3,
"correct_negatives": 636,
"pod": 0.1053,
"far": 0.4286,
"csi": 0.0976,
"forecasts_issued": 7
},
"cost_loss": [
{
"cost_loss_ratio": 0.05,
"value": 0.5962
},
{
"cost_loss_ratio": 0.1,
"value": 0.4532
},
{
"cost_loss_ratio": 0.15,
"value": 0.3947
},
{
"cost_loss_ratio": 0.2,
"value": 0.3289
},
{
"cost_loss_ratio": 0.25,
"value": 0.2982
},
{
"cost_loss_ratio": 0.3,
"value": 0.2632
},
{
"cost_loss_ratio": 0.35,
"value": 0.2227
},
{
"cost_loss_ratio": 0.4,
"value": 0.1754
},
{
"cost_loss_ratio": 0.45,
"value": 0.1196
},
{
"cost_loss_ratio": 0.5,
"value": 0.0526
},
{
"cost_loss_ratio": 0.55,
"value": 0.0351
},
{
"cost_loss_ratio": 0.6,
"value": 0.0132
},
{
"cost_loss_ratio": 0.65,
"value": 0.0
},
{
"cost_loss_ratio": 0.7,
"value": 0.0
},
{
"cost_loss_ratio": 0.75,
"value": 0.0
},
{
"cost_loss_ratio": 0.8,
"value": 0.0
},
{
"cost_loss_ratio": 0.85,
"value": 0.0
},
{
"cost_loss_ratio": 0.9,
"value": 0.0
},
{
"cost_loss_ratio": 0.95,
"value": 0.0
}
]
},
"dvorak_head": {
"status": "unvalidated",
"reason": "Scene labels are weak, derived from the IMD CI number rather than from the CIMSS ADT archive, which was not pulled. No hand-labelled seed set exists, so the head is trained and served but not scored."
}
}