Datasets:
Submit evaluation results for Toto-2.0-4m
#25
by chris-lettieri-dd - opened
This view is limited to 50 files because it contains too many changes. See the raw diff here.
- results/Toto-2.0-4m/Australia_Solar/H/long/config.json +40 -0
- results/Toto-2.0-4m/Australia_Solar/H/long/metrics.npz +3 -0
- results/Toto-2.0-4m/Australia_Solar/H/long/predictions.npz +3 -0
- results/Toto-2.0-4m/Australia_Solar/H/medium/config.json +40 -0
- results/Toto-2.0-4m/Australia_Solar/H/medium/metrics.npz +3 -0
- results/Toto-2.0-4m/Australia_Solar/H/medium/predictions.npz +3 -0
- results/Toto-2.0-4m/Australia_Solar/H/short/config.json +40 -0
- results/Toto-2.0-4m/Australia_Solar/H/short/metrics.npz +3 -0
- results/Toto-2.0-4m/Australia_Solar/H/short/predictions.npz +3 -0
- results/Toto-2.0-4m/Auto_Production_SF/M/short/config.json +40 -0
- results/Toto-2.0-4m/Auto_Production_SF/M/short/metrics.npz +3 -0
- results/Toto-2.0-4m/Auto_Production_SF/M/short/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/long/config.json +40 -0
- results/Toto-2.0-4m/CPHL/15T/long/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/long/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/medium/config.json +40 -0
- results/Toto-2.0-4m/CPHL/15T/medium/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/medium/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/short/config.json +40 -0
- results/Toto-2.0-4m/CPHL/15T/short/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/15T/short/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/long/config.json +40 -0
- results/Toto-2.0-4m/CPHL/30T/long/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/long/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/medium/config.json +40 -0
- results/Toto-2.0-4m/CPHL/30T/medium/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/medium/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/short/config.json +40 -0
- results/Toto-2.0-4m/CPHL/30T/short/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/30T/short/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/long/config.json +40 -0
- results/Toto-2.0-4m/CPHL/H/long/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/long/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/medium/config.json +40 -0
- results/Toto-2.0-4m/CPHL/H/medium/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/medium/predictions.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/short/config.json +40 -0
- results/Toto-2.0-4m/CPHL/H/short/metrics.npz +3 -0
- results/Toto-2.0-4m/CPHL/H/short/predictions.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/long/config.json +40 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/long/metrics.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/long/predictions.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/medium/config.json +40 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/medium/metrics.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/medium/predictions.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/short/config.json +40 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/short/metrics.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/15T/short/predictions.npz +3 -0
- results/Toto-2.0-4m/Coastal_T_S/20T/long/config.json +40 -0
- results/Toto-2.0-4m/Coastal_T_S/20T/long/metrics.npz +3 -0
results/Toto-2.0-4m/Australia_Solar/H/long/config.json
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{
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"dataset_config": "Australia_Solar/H/long",
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"num_series": 1,
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"num_windows": 15,
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"num_variates": 3,
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"prediction_length": 168,
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"num_quantiles": 9,
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"quantile_levels": [
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],
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"freq": "H",
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"seasonality": 24,
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"context_length": 4096,
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"metric_names": [
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"MSE",
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"MAE",
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"RMSE",
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"MAPE",
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"sMAPE",
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"MASE",
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"ND",
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"CRPS"
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],
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"prediction_scale_factor": 100.0,
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"model_name": "Toto-2.0-4m",
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
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"batch_size": 512,
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"decode_block_size": 0,
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"imputation_internal": "ffill",
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"scaler_fallback_min_obs": 8,
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"quantile_real_cap_k": 10000.0
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}
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results/Toto-2.0-4m/Australia_Solar/H/long/metrics.npz
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size 4534
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results/Toto-2.0-4m/Australia_Solar/H/long/predictions.npz
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version https://git-lfs.github.com/spec/v1
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size 123065
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results/Toto-2.0-4m/Australia_Solar/H/medium/config.json
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{
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"dataset_config": "Australia_Solar/H/medium",
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"num_series": 1,
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"num_windows": 35,
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"num_variates": 3,
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"prediction_length": 72,
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"num_quantiles": 9,
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"quantile_levels": [
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.8,
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0.9
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],
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"freq": "H",
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"seasonality": 24,
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"context_length": 4096,
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"metric_names": [
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"MSE",
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"MAE",
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"RMSE",
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"MAPE",
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"sMAPE",
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"MASE",
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"ND",
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"CRPS"
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],
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"prediction_scale_factor": 100.0,
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"model_name": "Toto-2.0-4m",
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
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"batch_size": 512,
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"decode_block_size": 0,
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"imputation_internal": "ffill",
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"scaler_fallback_min_obs": 8,
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"quantile_real_cap_k": 10000.0
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}
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results/Toto-2.0-4m/Australia_Solar/H/medium/metrics.npz
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size 8365
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results/Toto-2.0-4m/Australia_Solar/H/medium/predictions.npz
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version https://git-lfs.github.com/spec/v1
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size 123137
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results/Toto-2.0-4m/Australia_Solar/H/short/config.json
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{
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"dataset_config": "Australia_Solar/H/short",
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"num_series": 1,
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"num_windows": 105,
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"num_variates": 3,
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"prediction_length": 24,
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"num_quantiles": 9,
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"quantile_levels": [
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9
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],
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"freq": "H",
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"seasonality": 24,
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"context_length": 4096,
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"metric_names": [
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"MSE",
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"MAE",
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"RMSE",
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"MAPE",
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"sMAPE",
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"MASE",
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"ND",
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"CRPS"
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],
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"prediction_scale_factor": 100.0,
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"model_name": "Toto-2.0-4m",
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
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"batch_size": 512,
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"decode_block_size": 0,
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"imputation_internal": "ffill",
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"scaler_fallback_min_obs": 8,
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"quantile_real_cap_k": 10000.0
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}
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results/Toto-2.0-4m/Australia_Solar/H/short/metrics.npz
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size 20770
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results/Toto-2.0-4m/Australia_Solar/H/short/predictions.npz
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size 123294
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results/Toto-2.0-4m/Auto_Production_SF/M/short/config.json
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{
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"dataset_config": "Auto_Production_SF/M/short",
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"num_series": 1,
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"num_windows": 5,
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"num_variates": 1,
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"prediction_length": 12,
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"num_quantiles": 9,
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"quantile_levels": [
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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],
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"freq": "M",
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"seasonality": 12,
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"context_length": 4096,
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"metric_names": [
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"MSE",
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| 24 |
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"MAE",
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| 25 |
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"RMSE",
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"MAPE",
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"sMAPE",
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"MASE",
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"ND",
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"CRPS"
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],
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"prediction_scale_factor": 1.0,
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"model_name": "Toto-2.0-4m",
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
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"batch_size": 512,
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"decode_block_size": 0,
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"imputation_internal": "ffill",
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"scaler_fallback_min_obs": 8,
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"quantile_real_cap_k": 10000.0
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}
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results/Toto-2.0-4m/Auto_Production_SF/M/short/metrics.npz
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size 1824
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results/Toto-2.0-4m/Auto_Production_SF/M/short/predictions.npz
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version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 1320
|
results/Toto-2.0-4m/CPHL/15T/long/config.json
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
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|
|
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|
|
|
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|
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|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
|
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|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset_config": "CPHL/15T/long",
|
| 3 |
+
"num_series": 2,
|
| 4 |
+
"num_windows": 5,
|
| 5 |
+
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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| 11 |
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0.3,
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| 12 |
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| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
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"MAE",
|
| 25 |
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"RMSE",
|
| 26 |
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"MAPE",
|
| 27 |
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"sMAPE",
|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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}
|
results/Toto-2.0-4m/CPHL/15T/long/metrics.npz
ADDED
|
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size 2172
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results/Toto-2.0-4m/CPHL/15T/long/predictions.npz
ADDED
|
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| 3 |
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size 38409
|
results/Toto-2.0-4m/CPHL/15T/medium/config.json
ADDED
|
@@ -0,0 +1,40 @@
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|
|
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|
|
|
|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
|
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|
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|
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|
|
|
|
| 1 |
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{
|
| 2 |
+
"dataset_config": "CPHL/15T/medium",
|
| 3 |
+
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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"freq": "15T",
|
| 20 |
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|
| 21 |
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"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
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"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
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"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
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"ND",
|
| 30 |
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"CRPS"
|
| 31 |
+
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|
| 32 |
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"prediction_scale_factor": 1.0,
|
| 33 |
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"model_name": "Toto-2.0-4m",
|
| 34 |
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
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"batch_size": 512,
|
| 36 |
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|
| 37 |
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"imputation_internal": "ffill",
|
| 38 |
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"scaler_fallback_min_obs": 8,
|
| 39 |
+
"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/CPHL/15T/medium/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
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| 3 |
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size 3468
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results/Toto-2.0-4m/CPHL/15T/medium/predictions.npz
ADDED
|
@@ -0,0 +1,3 @@
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| 3 |
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|
results/Toto-2.0-4m/CPHL/15T/short/config.json
ADDED
|
@@ -0,0 +1,40 @@
|
|
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|
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|
|
|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
+
"dataset_config": "CPHL/15T/short",
|
| 3 |
+
"num_series": 2,
|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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|
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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"freq": "15T",
|
| 20 |
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|
| 21 |
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"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
+
"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
+
"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
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"ND",
|
| 30 |
+
"CRPS"
|
| 31 |
+
],
|
| 32 |
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"prediction_scale_factor": 1.0,
|
| 33 |
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"model_name": "Toto-2.0-4m",
|
| 34 |
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
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"batch_size": 512,
|
| 36 |
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|
| 37 |
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|
| 38 |
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"scaler_fallback_min_obs": 8,
|
| 39 |
+
"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/CPHL/15T/short/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
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| 3 |
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size 15762
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results/Toto-2.0-4m/CPHL/15T/short/predictions.npz
ADDED
|
@@ -0,0 +1,3 @@
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| 3 |
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size 40293
|
results/Toto-2.0-4m/CPHL/30T/long/config.json
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset_config": "CPHL/30T/long",
|
| 3 |
+
"num_series": 2,
|
| 4 |
+
"num_windows": 10,
|
| 5 |
+
"num_variates": 1,
|
| 6 |
+
"prediction_length": 144,
|
| 7 |
+
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|
| 8 |
+
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|
| 9 |
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|
| 10 |
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|
| 11 |
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| 12 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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],
|
| 19 |
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"freq": "30T",
|
| 20 |
+
"seasonality": 48,
|
| 21 |
+
"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
+
"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
+
"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
+
"ND",
|
| 30 |
+
"CRPS"
|
| 31 |
+
],
|
| 32 |
+
"prediction_scale_factor": 1.0,
|
| 33 |
+
"model_name": "Toto-2.0-4m",
|
| 34 |
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
+
"batch_size": 512,
|
| 36 |
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"decode_block_size": 0,
|
| 37 |
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"imputation_internal": "ffill",
|
| 38 |
+
"scaler_fallback_min_obs": 8,
|
| 39 |
+
"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/CPHL/30T/long/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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| 3 |
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size 2838
|
results/Toto-2.0-4m/CPHL/30T/long/predictions.npz
ADDED
|
@@ -0,0 +1,3 @@
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|
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| 1 |
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| 3 |
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size 40015
|
results/Toto-2.0-4m/CPHL/30T/medium/config.json
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
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|
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|
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|
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|
|
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|
|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset_config": "CPHL/30T/medium",
|
| 3 |
+
"num_series": 2,
|
| 4 |
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|
| 5 |
+
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|
| 6 |
+
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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"freq": "30T",
|
| 20 |
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"seasonality": 48,
|
| 21 |
+
"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
+
"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
+
"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
+
"ND",
|
| 30 |
+
"CRPS"
|
| 31 |
+
],
|
| 32 |
+
"prediction_scale_factor": 1.0,
|
| 33 |
+
"model_name": "Toto-2.0-4m",
|
| 34 |
+
"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
+
"batch_size": 512,
|
| 36 |
+
"decode_block_size": 0,
|
| 37 |
+
"imputation_internal": "ffill",
|
| 38 |
+
"scaler_fallback_min_obs": 8,
|
| 39 |
+
"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/CPHL/30T/medium/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
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|
|
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|
| 1 |
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|
| 3 |
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size 5461
|
results/Toto-2.0-4m/CPHL/30T/medium/predictions.npz
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
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|
|
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| 1 |
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| 3 |
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size 40649
|
results/Toto-2.0-4m/CPHL/30T/short/config.json
ADDED
|
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results/Toto-2.0-4m/CPHL/30T/short/metrics.npz
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results/Toto-2.0-4m/CPHL/H/long/config.json
ADDED
|
@@ -0,0 +1,40 @@
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| 23 |
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|
| 40 |
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|
results/Toto-2.0-4m/CPHL/H/long/metrics.npz
ADDED
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results/Toto-2.0-4m/CPHL/H/medium/config.json
ADDED
|
@@ -0,0 +1,40 @@
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|
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|
results/Toto-2.0-4m/CPHL/H/medium/metrics.npz
ADDED
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results/Toto-2.0-4m/CPHL/H/medium/predictions.npz
ADDED
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results/Toto-2.0-4m/CPHL/H/short/config.json
ADDED
|
@@ -0,0 +1,40 @@
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| 3 |
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|
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|
| 22 |
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|
| 23 |
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| 24 |
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|
| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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|
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|
| 40 |
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|
results/Toto-2.0-4m/CPHL/H/short/metrics.npz
ADDED
|
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results/Toto-2.0-4m/CPHL/H/short/predictions.npz
ADDED
|
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results/Toto-2.0-4m/Coastal_T_S/15T/long/config.json
ADDED
|
@@ -0,0 +1,40 @@
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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| 8 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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| 27 |
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| 28 |
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| 30 |
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|
| 31 |
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| 32 |
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|
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|
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| 38 |
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|
| 39 |
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|
| 40 |
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|
results/Toto-2.0-4m/Coastal_T_S/15T/long/metrics.npz
ADDED
|
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results/Toto-2.0-4m/Coastal_T_S/15T/long/predictions.npz
ADDED
|
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results/Toto-2.0-4m/Coastal_T_S/15T/medium/config.json
ADDED
|
@@ -0,0 +1,40 @@
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|
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|
|
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
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|
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|
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|
| 39 |
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|
| 40 |
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}
|
results/Toto-2.0-4m/Coastal_T_S/15T/medium/metrics.npz
ADDED
|
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| 3 |
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size 14852
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results/Toto-2.0-4m/Coastal_T_S/15T/medium/predictions.npz
ADDED
|
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| 3 |
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size 103243
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results/Toto-2.0-4m/Coastal_T_S/15T/short/config.json
ADDED
|
@@ -0,0 +1,40 @@
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset_config": "Coastal_T_S/15T/short",
|
| 3 |
+
"num_series": 5,
|
| 4 |
+
"num_windows": 120,
|
| 5 |
+
"num_variates": 3,
|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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],
|
| 19 |
+
"freq": "15T",
|
| 20 |
+
"seasonality": 96,
|
| 21 |
+
"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
+
"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
+
"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
+
"ND",
|
| 30 |
+
"CRPS"
|
| 31 |
+
],
|
| 32 |
+
"prediction_scale_factor": 1.0,
|
| 33 |
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"model_name": "Toto-2.0-4m",
|
| 34 |
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
+
"batch_size": 512,
|
| 36 |
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|
| 37 |
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"imputation_internal": "ffill",
|
| 38 |
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"scaler_fallback_min_obs": 8,
|
| 39 |
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"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/Coastal_T_S/15T/short/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
| 1 |
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| 3 |
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size 103033
|
results/Toto-2.0-4m/Coastal_T_S/15T/short/predictions.npz
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 133228
|
results/Toto-2.0-4m/Coastal_T_S/20T/long/config.json
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
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|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"dataset_config": "Coastal_T_S/20T/long",
|
| 3 |
+
"num_series": 1,
|
| 4 |
+
"num_windows": 5,
|
| 5 |
+
"num_variates": 3,
|
| 6 |
+
"prediction_length": 216,
|
| 7 |
+
"num_quantiles": 9,
|
| 8 |
+
"quantile_levels": [
|
| 9 |
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|
| 10 |
+
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|
| 11 |
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0.3,
|
| 12 |
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|
| 13 |
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0.5,
|
| 14 |
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0.6,
|
| 15 |
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0.7,
|
| 16 |
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0.8,
|
| 17 |
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0.9
|
| 18 |
+
],
|
| 19 |
+
"freq": "20T",
|
| 20 |
+
"seasonality": 72,
|
| 21 |
+
"context_length": 4096,
|
| 22 |
+
"metric_names": [
|
| 23 |
+
"MSE",
|
| 24 |
+
"MAE",
|
| 25 |
+
"RMSE",
|
| 26 |
+
"MAPE",
|
| 27 |
+
"sMAPE",
|
| 28 |
+
"MASE",
|
| 29 |
+
"ND",
|
| 30 |
+
"CRPS"
|
| 31 |
+
],
|
| 32 |
+
"prediction_scale_factor": 1.0,
|
| 33 |
+
"model_name": "Toto-2.0-4m",
|
| 34 |
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"model_weights_path": "s3://dd-data-science-us1-prod/ray/foundation-models/emaad/20260403_mup_pretrained_toto_v2_final_scaleup/tiny_pretrained_ps32-b3448c57/checkpoint_2026-04-10_15-44-59.160709",
|
| 35 |
+
"batch_size": 512,
|
| 36 |
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"decode_block_size": 0,
|
| 37 |
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"imputation_internal": "ffill",
|
| 38 |
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"scaler_fallback_min_obs": 8,
|
| 39 |
+
"quantile_real_cap_k": 10000.0
|
| 40 |
+
}
|
results/Toto-2.0-4m/Coastal_T_S/20T/long/metrics.npz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
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| 3 |
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size 2486
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