Submit evaluation results for TimesFM-3 (#39)

- Submit evaluation results for TimesFM-3 (db9efc24e6767f2677732a4a5817c82b7a026629)
- Submit evaluation results for TimesFM-3 (part 2) (1f3fc6d0ab830409bff057806e26697fbd704964)
- Update TimesFM-3 evaluation outputs (8fac7deb3e06af53def47901791603245643fe5f)
- Update TimesFM-3 evaluation outputs (part 2) (948fe51392e3b4a9cbe77f746a0c0f5616ab4bff)


Co-authored-by: Ayush Jain <ayujain25@users.noreply.huggingface.co>

results/TimesFM-3/Australia_Solar/H/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Australia_Solar/H/long",
+  "num_series": 1,
+  "num_windows": 15,
+  "num_variates": 3,
+  "prediction_length": 168,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 100.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Australia_Solar/H/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:540d540e5aac382bc3eba321f1a9c38d9d03626447f5d5d9b1791f16547a844d
+size 4536

results/TimesFM-3/Australia_Solar/H/long/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:84904a1e635539aee758e46d7fa83be477c71714d22390ecdf36b2a4c7fa45d4
+size 117194

results/TimesFM-3/Australia_Solar/H/medium/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Australia_Solar/H/medium",
+  "num_series": 1,
+  "num_windows": 35,
+  "num_variates": 3,
+  "prediction_length": 72,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 100.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Australia_Solar/H/medium/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b82f98c0648b490ed71cbb431a15deb194b3fc4bc8e0d47736c73e82df4d3636
+size 8351

results/TimesFM-3/Australia_Solar/H/medium/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e755619f453998902eca29a816c922643e93219b1db71b02d428c352696f3119
+size 117967

results/TimesFM-3/Australia_Solar/H/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Australia_Solar/H/short",
+  "num_series": 1,
+  "num_windows": 105,
+  "num_variates": 3,
+  "prediction_length": 24,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 100.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Australia_Solar/H/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3641594cacd2c415b62777083fb0a98adfb17dd8396287f43318aef6ec15779a
+size 20779

results/TimesFM-3/Australia_Solar/H/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:62193712225062b53bdfd260d1abed6bbee21620a79f77262c2799f4b54cc575
+size 117245

results/TimesFM-3/Auto_Production_SF/M/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Auto_Production_SF/M/short",
+  "num_series": 1,
+  "num_windows": 5,
+  "num_variates": 1,
+  "prediction_length": 12,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "M",
+  "seasonality": 12,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Auto_Production_SF/M/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e98a635ab425e17b5cd10c2034e9155c8d52e2fb6863309565e9504f7165ae51
+size 1821

results/TimesFM-3/Auto_Production_SF/M/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7998dcc0916bb168a0eee96475d7919489d254a3da957aa49faf079c23bb4d6d
+size 1313

results/TimesFM-3/CPHL/15T/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/15T/long",
+  "num_series": 2,
+  "num_windows": 5,
+  "num_variates": 1,
+  "prediction_length": 288,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/15T/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:73d2d7a6a4dd5cef67f8ada2a8715dbd30bd9a3cace309d34b90a5dabdcd3592
+size 2176

results/TimesFM-3/CPHL/15T/long/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38028b56163798af38888824b07ac10be51ba052738e6fcd08253c659ea45812
+size 38035

results/TimesFM-3/CPHL/15T/medium/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/15T/medium",
+  "num_series": 2,
+  "num_windows": 15,
+  "num_variates": 1,
+  "prediction_length": 96,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/15T/medium/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03d2c45d8999e360a61a96a67f542c7015d2a1654be939b217a0fa662e6eb7e0
+size 3464

results/TimesFM-3/CPHL/15T/medium/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8882a7bfba183a8eb62d85855b9f9e90a8a25162959cce9b7a5efc9e78a86cd9
+size 38814

results/TimesFM-3/CPHL/15T/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/15T/short",
+  "num_series": 2,
+  "num_windows": 120,
+  "num_variates": 1,
+  "prediction_length": 12,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/15T/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9d0a6e07e1f2aa29d7a8a52657af0ae1f5014000208904e6a2897f01201db64
+size 15734

results/TimesFM-3/CPHL/15T/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf54fcc4427f6d5a4ffa2a5f5480759ca342f237b3ee788397c97de0c86b1c5c
+size 40029

results/TimesFM-3/CPHL/30T/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/30T/long",
+  "num_series": 2,
+  "num_windows": 10,
+  "num_variates": 1,
+  "prediction_length": 144,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "30T",
+  "seasonality": 48,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/30T/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b68e0f7547183b8d148debc21b5492ced41c0400100d432b3de566cfac55d343
+size 2836

results/TimesFM-3/CPHL/30T/long/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:15360239f0c12211fe89ec986f8cec0b2e2c935e2372878fc159a35327d95509
+size 40097

results/TimesFM-3/CPHL/30T/medium/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/30T/medium",
+  "num_series": 2,
+  "num_windows": 30,
+  "num_variates": 1,
+  "prediction_length": 48,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "30T",
+  "seasonality": 48,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/30T/medium/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8aadbd1dfe3b23b3b0f52ba5c971da55824a9fb12a5ac38e57d6db3e1c80dda1
+size 5474

results/TimesFM-3/CPHL/30T/medium/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:790706b47cee55fa00695c375e2dfc6253e825f9a4968730dcbbdd18cfc658c9
+size 40662

results/TimesFM-3/CPHL/30T/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/30T/short",
+  "num_series": 2,
+  "num_windows": 120,
+  "num_variates": 1,
+  "prediction_length": 12,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "30T",
+  "seasonality": 48,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/30T/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6e4d15674a53f6007be6f16fa5a3641301f3baff4ed9c575e413cc072c0faa6
+size 15887

results/TimesFM-3/CPHL/30T/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8842a010eb6e947f94b853c99adf40b6d3c06f1dff7548e7f796d3b1d8554d9a
+size 41457

results/TimesFM-3/CPHL/H/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/H/long",
+  "num_series": 4,
+  "num_windows": 2,
+  "num_variates": 1,
+  "prediction_length": 336,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/H/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d5621c4e22922e582adb2902bf91463b79569fba77029cb54892ac6243f1fc3d
+size 2040

results/TimesFM-3/CPHL/H/long/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0847753f7da7544d54b074e8f25b5283ff9b33ad5102726391caee4490660e7
+size 38111

results/TimesFM-3/CPHL/H/medium/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/H/medium",
+  "num_series": 4,
+  "num_windows": 4,
+  "num_variates": 1,
+  "prediction_length": 168,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/H/medium/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c56b0546a306d5f20acbe8494df5483db7f811ac3c8052c2c8531aa0e889787
+size 2558

results/TimesFM-3/CPHL/H/medium/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5da46cf906413f632fd5ae00dc75ddadb1027446a97006207985490f0271ac93
+size 38415

results/TimesFM-3/CPHL/H/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "CPHL/H/short",
+  "num_series": 4,
+  "num_windows": 28,
+  "num_variates": 1,
+  "prediction_length": 24,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "H",
+  "seasonality": 24,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/CPHL/H/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:80efc062127f13ba8c2fd4d40309730b496cf93791af256d5d7f6da578497fa9
+size 8516

results/TimesFM-3/CPHL/H/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7959b68f4b35e9cb964ccddc10790eb0dd526d26a01e414ab12a6dd64d7bf434
+size 39193

results/TimesFM-3/Coastal_T_S/15T/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Coastal_T_S/15T/long",
+  "num_series": 5,
+  "num_windows": 5,
+  "num_variates": 3,
+  "prediction_length": 288,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Coastal_T_S/15T/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb648d58c1300104376888571dd4f023500f10041f67558293d3f988c8fbbc49
+size 6274

results/TimesFM-3/Coastal_T_S/15T/long/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:afeaa84e040ac975854818550f6fc646dc393a208cb1eccd29666179e185286c
+size 69490

results/TimesFM-3/Coastal_T_S/15T/medium/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Coastal_T_S/15T/medium",
+  "num_series": 5,
+  "num_windows": 15,
+  "num_variates": 3,
+  "prediction_length": 96,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Coastal_T_S/15T/medium/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:88d980e9a8c11538f9516c9c95b52104ddf79c51c194d4b34e802ee17771fcbc
+size 14821

results/TimesFM-3/Coastal_T_S/15T/medium/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78a5d1c1d076a6cfc27b47e533a2cf56717a3d61bd3e1a31dab51f5286518b26
+size 81880

results/TimesFM-3/Coastal_T_S/15T/short/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Coastal_T_S/15T/short",
+  "num_series": 5,
+  "num_windows": 120,
+  "num_variates": 3,
+  "prediction_length": 12,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "15T",
+  "seasonality": 96,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Coastal_T_S/15T/short/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a5c2c2c404bb7d645d6a18ecefe3c181e8f9a5f3c0b1aaebadc9da85f7d63c82
+size 102814

results/TimesFM-3/Coastal_T_S/15T/short/predictions.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7740e3c707fa68d32dae5e5d0c62a9107e1cdb372a0802a49f0e6cdfa66d7d94
+size 120630

results/TimesFM-3/Coastal_T_S/20T/long/config.json

@@ -0,0 +1,35 @@
+{
+  "dataset_config": "Coastal_T_S/20T/long",
+  "num_series": 1,
+  "num_windows": 5,
+  "num_variates": 3,
+  "prediction_length": 216,
+  "num_quantiles": 9,
+  "quantile_levels": [
+    0.1,
+    0.2,
+    0.3,
+    0.4,
+    0.5,
+    0.6,
+    0.7,
+    0.8,
+    0.9
+  ],
+  "freq": "20T",
+  "seasonality": 72,
+  "context_length": 15360,
+  "metric_names": [
+    "MSE",
+    "MAE",
+    "RMSE",
+    "MAPE",
+    "sMAPE",
+    "MASE",
+    "ND",
+    "CRPS"
+  ],
+  "prediction_scale_factor": 1.0,
+  "model": "TimesFM-3",
+  "use_variate_attention": true
+}

results/TimesFM-3/Coastal_T_S/20T/long/metrics.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7751b826de20d0cec0a65d6d0df05eb104463cf8bf70f8b145507cd25d6ba098
+size 2489