Revert: remove incorrectly added root leaderboards and breakdown_tabels folder

boom_leaderboard.csv

@@ -1,24 +0,0 @@
-model,MASE-6750-scaled,CRPS-6750-scaled,Rank-6750-scaled,eval_metrics/MAE[0.5]-663-unscaled,CRPS-663-unscaled,Rank-663-unscaled
-toto_2.0_2.5b,0.581,0.353,3.902,0.000,0.001,5.299
-toto_2.0_1b,0.582,0.351,4.006,0.000,0.001,7.178
-toto_2.0_313m,0.586,0.353,4.371,0.000,0.001,6.253
-toto_2.0_22m,0.601,0.365,5.558,0.000,0.001,8.585
-toto,0.617,0.375,6.926,0.001,0.025,14.449
-toto_2.0_4m,0.624,0.378,7.175,0.000,0.001,5.940
-chronos_2,0.641,0.392,7.367,0.000,0.002,12.306
-timesfm_2_5_200m,0.632,0.382,7.680,0.000,0.001,8.477
-moirai_1.1_base,0.710,0.428,10.375,0.000,0.003,12.443
-moirai_1.1_large,0.720,0.436,10.727,0.001,0.005,13.780
-moirai_1.1_small,0.729,0.442,11.228,0.000,0.006,14.267
-moirai_2_small,0.672,0.427,11.273,0.001,0.002,12.931
-timesfm_2_0_500m,0.725,0.447,11.900,0.014,0.091,17.913
-chronos_bolt_base,0.726,0.451,12.321,0.003,0.019,15.487
-chronos_bolt_small,0.733,0.455,12.725,0.003,0.022,15.621
-autoarima,0.824,0.736,17.128,0.000,0.001,6.798
-time_moe_50M,0.806,0.649,17.514,0.001,0.005,12.982
-time_moe_200M,0.881,0.643,17.531,0.000,0.005,15.371
-timer,0.796,0.639,17.581,0.001,0.005,11.457
-visionts,0.988,0.673,18.721,0.001,0.009,16.575
-autoets,0.842,1.975,19.349,0.000,0.030,13.398
-autotheta,1.123,1.018,20.233,0.001,0.002,11.638
-seasonalnaive,1.000,1.000,20.410,0.000,0.006,16.852

boomlet_leaderboard.csv

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-model,MASE-90-scaled,CRPS-90-scaled,Rank-90-scaled,eval_metrics/MAE[0.5]-6-unscaled,CRPS-6-unscaled,Rank-6-unscaled
-toto_2.0_2.5b,0.583,0.485,2.589,0.106,0.274,1.833
-toto_2.0_1b,0.585,0.485,2.600,0.106,0.272,1.333
-toto_2.0_313m,0.586,0.485,2.811,0.107,0.279,2.833
-toto_2.0_22m,0.601,0.500,4.389,0.111,0.290,4.000
-toto_2.0_4m,0.624,0.517,5.967,0.116,0.305,6.167
-toto,0.617,0.519,6.411,0.116,0.333,7.167
-chronos_2,0.623,0.522,6.711,0.123,0.359,8.167
-timesfm_2_5_200m,0.638,0.532,7.722,0.121,0.319,8.167
-moirai_1.1_large,0.767,0.621,11.478,0.202,0.624,15.000
-timesfm_2_0_500m,0.685,0.603,11.511,0.150,0.390,10.833
-moirai_1.1_base,0.779,0.630,11.767,0.203,0.537,12.500
-moirai_1.1_small,0.786,0.631,12.133,0.202,0.548,13.000
-moirai_2_small,0.902,0.467,12.278,0.168,0.928,15.500
-chronos_bolt_base,0.711,0.637,12.844,0.213,0.563,13.667
-chronos_bolt_small,0.717,0.642,13.078,0.176,0.468,11.333
-time_moe_200M,0.793,0.780,17.178,0.230,1.056,15.000
-time_moe_50M,0.810,0.788,17.222,0.244,1.123,16.333
-timer,0.807,0.793,17.622,0.296,1.363,19.333
-autoarima,0.922,0.880,18.011,0.350,1.255,17.500
-visionts,0.912,0.885,19.600,0.365,1.047,18.833
-seasonalnaive,1.000,1.000,20.122,0.217,0.952,15.500
-autoets,0.969,15.664,20.756,0.275,1.865,20.667
-autotheta,1.030,1.182,21.200,0.383,2.290,21.333

breakdown_tabels/domain_CRPS_shifted_gmean.csv

@@ -1,24 +0,0 @@
-model,Application Usage,Database,Infrastructure,Networking,Security
-autoarima,0.757,0.734,0.679,0.795,0.757
-autoets,1.423,1.604,4.563,2.067,0.878
-autotheta,1.019,1.032,0.963,1.105,0.991
-chronos_2,0.387,0.381,0.423,0.416,0.467
-chronos_bolt_base,0.451,0.441,0.466,0.489,0.535
-chronos_bolt_small,0.452,0.444,0.474,0.506,0.539
-moirai_1.1_base,0.422,0.414,0.446,0.484,0.504
-moirai_1.1_large,0.43,0.418,0.462,0.484,0.504
-moirai_1.1_small,0.438,0.425,0.462,0.503,0.507
-moirai_2_small,0.432,0.427,0.42,0.487,0.508
-seasonalnaive,1.0,1.0,1.0,1.0,1.0
-time_moe_200M,0.611,0.633,0.71,0.739,0.629
-time_moe_50M,0.633,0.618,0.713,0.721,0.625
-timer,0.636,0.619,0.655,0.725,0.664
-timesfm_2_0_500m,0.441,0.44,0.471,0.493,0.525
-timesfm_2_5_200m,0.384,0.372,0.397,0.408,0.476
-toto,0.378,0.362,0.391,0.4,0.476
-toto_2.0_1b,0.352,0.335,0.369,0.382,0.454
-toto_2.0_2.5b,0.353,0.339,0.371,0.382,0.456
-toto_2.0_22m,0.367,0.349,0.38,0.391,0.462
-toto_2.0_313m,0.357,0.34,0.366,0.381,0.453
-toto_2.0_4m,0.382,0.361,0.39,0.406,0.473
-visionts,0.692,0.637,0.663,0.736,0.735

breakdown_tabels/domain_MASE_shifted_gmean.csv

@@ -1,24 +0,0 @@
-model,Application Usage,Database,Infrastructure,Networking,Security
-autoarima,0.865,0.839,0.708,0.937,0.9
-autoets,0.87,0.859,0.727,0.98,0.868
-autotheta,1.151,1.188,0.976,1.213,1.039
-chronos_2,0.657,0.656,0.604,0.657,0.671
-chronos_bolt_base,0.748,0.757,0.663,0.757,0.729
-chronos_bolt_small,0.748,0.761,0.678,0.779,0.734
-moirai_1.1_base,0.721,0.738,0.65,0.786,0.739
-moirai_1.1_large,0.73,0.743,0.67,0.773,0.736
-moirai_1.1_small,0.74,0.741,0.675,0.807,0.748
-moirai_2_small,0.714,0.616,0.657,0.77,0.735
-seasonalnaive,1.0,1.0,1.0,1.0,1.0
-time_moe_200M,0.884,0.903,0.847,0.933,0.776
-time_moe_50M,0.863,0.714,0.791,0.856,0.77
-timer,0.871,0.716,0.728,0.871,0.828
-timesfm_2_0_500m,0.736,0.765,0.679,0.765,0.717
-timesfm_2_5_200m,0.654,0.655,0.577,0.65,0.686
-toto,0.639,0.635,0.567,0.635,0.682
-toto_2.0_1b,0.603,0.596,0.536,0.605,0.654
-toto_2.0_2.5b,0.601,0.595,0.534,0.61,0.654
-toto_2.0_22m,0.623,0.613,0.552,0.627,0.666
-toto_2.0_313m,0.607,0.6,0.539,0.611,0.651
-toto_2.0_4m,0.648,0.642,0.569,0.652,0.68
-visionts,1.044,1.003,0.858,1.045,0.92

breakdown_tabels/full_benchmark_CRPS_shifted_gmean.csv

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-model,full_benchmark
-autoarima,0.736
-autoets,1.975
-autotheta,1.018
-chronos_2,0.392
-chronos_bolt_base,0.451
-chronos_bolt_small,0.455
-moirai_1.1_base,0.428
-moirai_1.1_large,0.436
-moirai_1.1_small,0.442
-moirai_2_small,0.427
-seasonalnaive,1.0
-time_moe_200M,0.643
-time_moe_50M,0.649
-timer,0.639
-timesfm_2_0_500m,0.447
-timesfm_2_5_200m,0.382
-toto,0.375
-toto_2.0_1b,0.351
-toto_2.0_2.5b,0.353
-toto_2.0_22m,0.365
-toto_2.0_313m,0.353
-toto_2.0_4m,0.378
-visionts,0.673

breakdown_tabels/full_benchmark_MASE_shifted_gmean.csv

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-model,full_benchmark
-autoarima,0.824
-autoets,0.842
-autotheta,1.123
-chronos_2,0.641
-chronos_bolt_base,0.726
-chronos_bolt_small,0.733
-moirai_1.1_base,0.71
-moirai_1.1_large,0.72
-moirai_1.1_small,0.729
-moirai_2_small,0.672
-seasonalnaive,1.0
-time_moe_200M,0.881
-time_moe_50M,0.806
-timer,0.796
-timesfm_2_0_500m,0.725
-timesfm_2_5_200m,0.632
-toto,0.617
-toto_2.0_1b,0.582
-toto_2.0_2.5b,0.581
-toto_2.0_22m,0.601
-toto_2.0_313m,0.586
-toto_2.0_4m,0.624
-visionts,0.988

breakdown_tabels/real_term_CRPS_shifted_gmean.csv

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-model,long,medium,short
-autoarima,0.807,0.804,0.634
-autoets,2.83,2.399,1.253
-autotheta,1.296,1.183,0.738
-chronos_2,0.444,0.426,0.33
-chronos_bolt_base,0.519,0.507,0.365
-chronos_bolt_small,0.528,0.508,0.368
-moirai_1.1_base,0.473,0.46,0.37
-moirai_1.1_large,0.491,0.475,0.369
-moirai_1.1_small,0.485,0.475,0.387
-moirai_2_small,0.47,0.458,0.373
-seasonalnaive,1.0,1.0,1.0
-time_moe_200M,0.694,0.692,0.57
-time_moe_50M,0.724,0.725,0.541
-timer,0.661,0.671,0.597
-timesfm_2_0_500m,0.522,0.499,0.359
-timesfm_2_5_200m,0.424,0.411,0.331
-toto,0.424,0.406,0.318
-toto_2.0_1b,0.399,0.379,0.296
-toto_2.0_2.5b,0.402,0.382,0.297
-toto_2.0_22m,0.413,0.395,0.308
-toto_2.0_313m,0.399,0.383,0.3
-toto_2.0_4m,0.426,0.409,0.32
-visionts,0.698,0.694,0.637

breakdown_tabels/real_term_MASE_shifted_gmean.csv

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-model,long,medium,short
-autoarima,0.895,0.853,0.749
-autoets,0.938,0.885,0.739
-autotheta,1.368,1.163,0.928
-chronos_2,0.71,0.68,0.562
-chronos_bolt_base,0.798,0.782,0.632
-chronos_bolt_small,0.813,0.782,0.637
-moirai_1.1_base,0.78,0.753,0.627
-moirai_1.1_large,0.799,0.77,0.626
-moirai_1.1_small,0.797,0.769,0.649
-moirai_2_small,0.693,0.685,0.646
-seasonalnaive,1.0,1.0,1.0
-time_moe_200M,0.95,0.929,0.794
-time_moe_50M,0.886,0.866,0.704
-timer,0.809,0.804,0.779
-timesfm_2_0_500m,0.817,0.78,0.619
-timesfm_2_5_200m,0.7,0.67,0.554
-toto,0.688,0.657,0.535
-toto_2.0_1b,0.654,0.618,0.502
-toto_2.0_2.5b,0.653,0.618,0.501
-toto_2.0_22m,0.671,0.642,0.52
-toto_2.0_313m,0.657,0.622,0.507
-toto_2.0_4m,0.695,0.663,0.543
-visionts,1.028,1.006,0.943

breakdown_tabels/type_CRPS_shifted_gmean.csv

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-model,count,distribution,gauge,rate
-autoarima,0.767,0.736,0.701,0.777
-autoets,1.557,1.22,3.059,1.496
-autotheta,1.132,0.976,1.015,1.034
-chronos_2,0.338,0.384,0.409,0.38
-chronos_bolt_base,0.402,0.446,0.463,0.443
-chronos_bolt_small,0.403,0.452,0.469,0.445
-moirai_1.1_base,0.353,0.422,0.444,0.418
-moirai_1.1_large,0.372,0.428,0.456,0.422
-moirai_1.1_small,0.379,0.432,0.459,0.433
-moirai_2_small,0.398,0.428,0.427,0.429
-seasonalnaive,1.0,1.0,1.0,1.0
-time_moe_200M,0.698,0.596,0.703,0.596
-time_moe_50M,0.651,0.604,0.694,0.619
-timer,0.662,0.608,0.658,0.63
-timesfm_2_0_500m,0.403,0.44,0.466,0.431
-timesfm_2_5_200m,0.325,0.384,0.386,0.382
-toto,0.317,0.382,0.382,0.369
-toto_2.0_1b,0.289,0.359,0.353,0.351
-toto_2.0_2.5b,0.303,0.36,0.355,0.351
-toto_2.0_22m,0.313,0.373,0.367,0.362
-toto_2.0_313m,0.281,0.364,0.354,0.353
-toto_2.0_4m,0.313,0.38,0.379,0.38
-visionts,0.591,0.672,0.674,0.68

breakdown_tabels/type_MASE_shifted_gmean.csv

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-model,count,distribution,gauge,rate
-autoarima,1.031,0.864,0.755,0.88
-autoets,1.074,0.854,0.774,0.907
-autotheta,1.578,1.144,1.062,1.158
-chronos_2,0.714,0.674,0.614,0.654
-chronos_bolt_base,0.88,0.753,0.696,0.739
-chronos_bolt_small,0.883,0.759,0.706,0.742
-moirai_1.1_base,0.795,0.724,0.686,0.728
-moirai_1.1_large,0.813,0.729,0.7,0.733
-moirai_1.1_small,0.808,0.737,0.704,0.75
-moirai_2_small,0.686,0.745,0.616,0.711
-seasonalnaive,1.0,1.0,1.0,1.0
-time_moe_200M,1.035,0.877,0.89,0.862
-time_moe_50M,0.652,0.878,0.76,0.846
-timer,0.663,0.89,0.721,0.864
-timesfm_2_0_500m,0.919,0.745,0.706,0.726
-timesfm_2_5_200m,0.71,0.672,0.591,0.659
-toto,0.687,0.658,0.583,0.634
-toto_2.0_1b,0.633,0.627,0.541,0.608
-toto_2.0_2.5b,0.639,0.622,0.541,0.607
-toto_2.0_22m,0.67,0.647,0.56,0.626
-toto_2.0_313m,0.631,0.632,0.546,0.61
-toto_2.0_4m,0.704,0.664,0.584,0.65
-visionts,1.199,1.03,0.925,1.032