Datasets:
Add KernelSynth training data
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- README.md +23 -7
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README.md
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dataset_size: 57560596
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license: Apache 2.0
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homepage: https://github.com/mbohlkeschneider/gluon-ts/tree/mv_release/datasets
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- config_name:
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features:
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- name: target
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sequence: float64
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data_files:
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- split: train
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path: taxi_30min/train-*
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- config_name:
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data_files:
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- split: train
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path: tsmixup_10m/train-*
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- config_name: uber_tlc_daily
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data_files:
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- split: train
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ds = datasets.load_dataset("autogluon/chronos_datasets", "weatherbench_hourly_temperature", streaming=True, split="train")
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```
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## Chronos training
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The
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```python
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ds = datasets.load_dataset("autogluon/chronos_datasets", "
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```
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Note that since data in the
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## License
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dataset_size: 57560596
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license: Apache 2.0
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homepage: https://github.com/mbohlkeschneider/gluon-ts/tree/mv_release/datasets
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- config_name: training_corpus_kernel_synth_1m
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features:
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- name: target
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sequence: float64
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- name: id
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dtype: string
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- name: timestamp
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sequence: timestamp[ms]
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splits:
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- name: train
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num_examples: 1000000
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download_size: 8313239368
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- config_name: training_corpus_tsmixup_10m
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features:
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- name: target
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sequence: float64
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data_files:
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- split: train
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path: taxi_30min/train-*
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- config_name: training_corpus_kernel_synth_1m
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data_files:
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- split: train
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path: training_corpus/kernel_synth_1m/train-*
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- config_name: training_corpus_tsmixup_10m
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data_files:
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- split: train
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path: training_corpus/tsmixup_10m/train-*
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- config_name: uber_tlc_daily
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data_files:
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- split: train
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ds = datasets.load_dataset("autogluon/chronos_datasets", "weatherbench_hourly_temperature", streaming=True, split="train")
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```
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## Chronos training corpus with TSMixup & KernelSynth
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The training corpus used for training the Chronos models can be loaded via the configs `training_corpus_tsmixup_10m` (10M TSMixup augmentations of real-world data) and `training_corpus_kernel_synth_1m` (1M synthetic time series generated with KernelSynth), e.g.,
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```python
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ds = datasets.load_dataset("autogluon/chronos_datasets", "training_corpus_tsmixup_10m", streaming=True, split="train")
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```
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Note that since data in the training corpus was obtained by combining various synthetic & real-world time series, the timestamps contain dummy values that have no connection to the original data.
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## License
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