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TIME-Output

Tasks:
Time Series Forecasting
Modalities:
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Formats:
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Size:
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Tags:
time-series
forecasting
benchmark
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quickbrownfawkes zqiao11 YunshiWen Twinkles01 xjjneversaynever chris-lettieri-dd shengp666 commited on
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Add OmniScient results (fine-tuned Chronos-2 derivative, 360 Labs)

Browse files

LoRA fine-tune of amazon/chronos-2 on a small proprietary corpus of anonymized business time series. No TIME data, no TIME upstream sources, no public benchmark corpora used in fine-tuning. All 98 tasks, current dataset version, unmodified timebench metrics. Full disclosure in the discussion comment.


Co-authored-by: zqiao11 <zqiao11@users.noreply.huggingface.co>
Co-authored-by: YunshiWen <YunshiWen@users.noreply.huggingface.co>
Co-authored-by: Twinkles01 <Twinkles01@users.noreply.huggingface.co>
Co-authored-by: xjjneversaynever <xjjneversaynever@users.noreply.huggingface.co>
Co-authored-by: chris-lettieri-dd <chris-lettieri-dd@users.noreply.huggingface.co>
Co-authored-by: shengp666 <shengp666@users.noreply.huggingface.co>

This view is limited to 50 files because it contains too many changes.   See raw diff
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  1. .gitattributes +61 -0
  2. README.md +28 -0
  3. features/Australia_Solar/H/test.csv +3 -0
  4. features/Auto_Production_SF/M/full.csv +3 -0
  5. features/CPHL/15T/test.csv +3 -0
  6. features/CPHL/30T/test.csv +3 -0
  7. features/CPHL/H/test.csv +3 -0
  8. features/Coastal_T_S/15T/test.csv +3 -0
  9. features/Coastal_T_S/20T/test.csv +3 -0
  10. features/Coastal_T_S/5T/test.csv +3 -0
  11. features/Coastal_T_S/H/test.csv +3 -0
  12. features/Commodity_Import/M/full.csv +3 -0
  13. features/Commodity_Production/M/full.csv +3 -0
  14. features/Crypto/D/full.csv +3 -0
  15. features/ECDC_COVID/D/full.csv +3 -0
  16. features/ECDC_COVID/W/full.csv +3 -0
  17. features/EWELD_Load/15T/test.csv +3 -0
  18. features/Finland_Traffic/15T/test.csv +3 -0
  19. features/Global_Influenza/W/full.csv +3 -0
  20. features/Global_Price/Q/full.csv +3 -0
  21. features/Housing_Inventory/M/full.csv +3 -0
  22. features/JOLTS/M/full.csv +3 -0
  23. features/Job_Claims/W/full.csv +3 -0
  24. features/MetroPT-3/5T/test.csv +3 -0
  25. features/NE_China_Wind/H/test.csv +3 -0
  26. features/Oil_Price/B/test.csv +3 -0
  27. features/Online_Retail_2_UCI/D/full.csv +3 -0
  28. features/OpenElectricity_NEM/5T/test.csv +3 -0
  29. features/Port_Activity/D/full.csv +3 -0
  30. features/Port_Activity/W/full.csv +3 -0
  31. features/SG_Carpark/15T/test.csv +3 -0
  32. features/SG_PM25/H/test.csv +3 -0
  33. features/SG_Weather/D/full.csv +3 -0
  34. features/Smart_Manufacturing/H/full.csv +3 -0
  35. features/Supply_Chain_Customer/D/full.csv +3 -0
  36. features/Supply_Chain_Location/D/full.csv +3 -0
  37. features/US_Labor/M/full.csv +3 -0
  38. features/US_Term_Structure/B/test.csv +3 -0
  39. features/Uncertainty_1M/M/full.csv +3 -0
  40. features/Vehicle_Sales/M/full.csv +3 -0
  41. features/Vehicle_Supply/M/full.csv +3 -0
  42. features/WUI_Global/Q/full.csv +3 -0
  43. features/Water_Quality_Darwin/15T/test.csv +3 -0
  44. features/azure2019_D/5T/test.csv +3 -0
  45. features/azure2019_I/5T/test.csv +3 -0
  46. features/azure2019_U/5T/full.csv +3 -0
  47. features/current_velocity/10T/test.csv +3 -0
  48. features/current_velocity/15T/test.csv +3 -0
  49. features/current_velocity/20T/test.csv +3 -0
  50. features/current_velocity/5T/test.csv +3 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ task_categories:
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+ - time-series-forecasting # 这是让系统识别为时间序列任务的关键
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+ tags: # 自定义标签
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+ - time-series
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+ - forecasting
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+ - benchmark
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+ ---
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+
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+ This repository contains the extracted time series features (tsfeatures) for each variate and the detailed forecasting results for every experiment.
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+
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+ **Note**: These files are for building leaderboard and visualization; users do not need to download this directory.
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+
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+ * `features/`: **Statistical Features (tsfeatures)**
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+
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+ Each dataset's features are saved to: `output/features/{dataset}/{freq}/`.
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+ This directory stores the computed tsfeatures for the variates in the dataset. The folder contains a CSV file named either:
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+ * `test.csv`: Features calculated on the **test split**.
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+ * `full.csv`: Features calculated on the **full dataset**.
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+
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+ * `results/`: **Experimental Results**
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+
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+ Each experiment is saved to: `output/results/{model}/{dataset}/{freq}/{horizon}/`.
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+ Each directory represents a specific model-dataset-frequency-horizon combination and contains the following files:
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+ * `config.json`: The experiment settings and hyperparameters.
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+ * `metrics.npz`: Window-level forecasting metrics (e.g., MASE, CRPS).
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+ * `predictions.npz`: Quantile prediction results for each sliding window.
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