mirror of
https://github.com/amazon-science/chronos-forecasting
synced 2026-05-23 09:39:35 +00:00
72ab64166c
*Issue #, if available:* N/A *Description of changes:* This PR adds support for Chronos-Bolt models. TODOs: - [x] Update evaluation script - [x] Fix and add tests for Bolt - [x] Update docstrings - [x] Update README example and mention Chronos-Bolt - [x] Update results bar plot in README - [x] Add versions for libraries in `pyproject.toml` - [x] Check that the training and eval scripts work - [x] Change `autogluon` -> `amazon` in model names Post Merge: - [ ] Update Citation style in README, both Github and HuggingFace repos - [ ] Remove note about AutoGluon - [ ] Update READMEs of original Chronos models to refer to Chronos-Bolt NOTE: To be merged after Chronos-Bolt models are available under the `amazon` namespace on HF. By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice. --------- Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de> Co-authored-by: Caner Turkmen <turkmen.ac@gmail.com> Co-authored-by: Lorenzo Stella <stellalo@amazon.com>
2.1 KiB
2.1 KiB
| 1 | dataset | model | MASE | WQL |
|---|---|---|---|---|
| 2 | ETTh | amazon/chronos-bolt-base | 0.7479154031956647 | 0.07062173821055001 |
| 3 | ETTm | amazon/chronos-bolt-base | 0.6334357237512225 | 0.052261607745858835 |
| 4 | dominick | amazon/chronos-bolt-base | 0.8560272479913918 | 0.3453573743726445 |
| 5 | ercot | amazon/chronos-bolt-base | 0.6933217425507392 | 0.02142183038021456 |
| 6 | exchange_rate | amazon/chronos-bolt-base | 1.7095176257412634 | 0.01200682136751536 |
| 7 | m4_quarterly | amazon/chronos-bolt-base | 1.2244670010522907 | 0.0771066518089854 |
| 8 | m4_yearly | amazon/chronos-bolt-base | 3.513752058541554 | 0.12142798053483984 |
| 9 | m5 | amazon/chronos-bolt-base | 0.9152230096463854 | 0.561999688057527 |
| 10 | monash_australian_electricity | amazon/chronos-bolt-base | 0.7403239930185613 | 0.03584034231329335 |
| 11 | monash_car_parts | amazon/chronos-bolt-base | 0.8550263912438314 | 0.9945122291263591 |
| 12 | monash_cif_2016 | amazon/chronos-bolt-base | 0.9988541862779904 | 0.016456104842296485 |
| 13 | monash_covid_deaths | amazon/chronos-bolt-base | 38.901749109066415 | 0.047410971217640714 |
| 14 | monash_fred_md | amazon/chronos-bolt-base | 0.6468787708795645 | 0.04185083716355386 |
| 15 | monash_hospital | amazon/chronos-bolt-base | 0.6883138394434054 | 0.057032869931903894 |
| 16 | monash_m1_monthly | amazon/chronos-bolt-base | 1.0997677446267855 | 0.1392311148066238 |
| 17 | monash_m1_quarterly | amazon/chronos-bolt-base | 1.7737851980875563 | 0.1007118219350403 |
| 18 | monash_m1_yearly | amazon/chronos-bolt-base | 4.404672537832342 | 0.1504617654430952 |
| 19 | monash_m3_monthly | amazon/chronos-bolt-base | 0.8510696834878182 | 0.09269673913736748 |
| 20 | monash_m3_quarterly | amazon/chronos-bolt-base | 1.2890908822598466 | 0.07615133571216029 |
| 21 | monash_m3_yearly | amazon/chronos-bolt-base | 2.9067097980770082 | 0.12934285625258413 |
| 22 | monash_nn5_weekly | amazon/chronos-bolt-base | 0.9158766337957451 | 0.08352114810139548 |
| 23 | monash_tourism_monthly | amazon/chronos-bolt-base | 1.5283388458731357 | 0.09026425492612797 |
| 24 | monash_tourism_quarterly | amazon/chronos-bolt-base | 1.756127005530011 | 0.06448060953595125 |
| 25 | monash_tourism_yearly | amazon/chronos-bolt-base | 3.691545772463519 | 0.16548820700844424 |
| 26 | monash_traffic | amazon/chronos-bolt-base | 0.7843310867739336 | 0.23148632068725078 |
| 27 | monash_weather | amazon/chronos-bolt-base | 0.8115247139672316 | 0.13350830777170594 |
| 28 | nn5 | amazon/chronos-bolt-base | 0.5764084996361287 | 0.1500519584148468 |