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  ---
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  license: mit
 
 
 
 
 
 
 
 
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  dataset_info:
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  - config_name: full_0
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  features:
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  - split: test
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  path: sub50_66/test-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ size_categories:
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+ - 10K<n<100K
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+ tags:
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+ - astronomy
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+ - multimodal
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+ - classification
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+ arxiv:
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+ - arXiv:2411.08842
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  dataset_info:
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  - config_name: full_0
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  features:
 
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  - split: test
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  path: sub50_66/test-*
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  ---
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+ # AstroM3Dataset
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+
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+ ## Description
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+ AstroM3Processed is a time-series astronomy dataset containing photometry, spectra, and metadata features for variable stars.
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+ The dataset includes multiple subsets (`full`, `sub10`, `sub25`, `sub50`) and supports different random seeds (`42`, `66`, `0`, `12`, `123`).
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+ Each sample consists of:
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+
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+ - **Photometry**: Light curve data of shape `(N, 9)` (time, flux, flux\_error, amplitude, period, lksl_statistic, rfr_score, mad, delta_t).
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+ - **Spectra**: Spectra observations of shape `(3, 2575)` (wavelength, flux, flux\_error).
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+ - **Metadata**: List of metadata values of shape `(34,)`
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+ - **Label**: The class name as int.
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+
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+ ## Corresponding paper and code
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+ - Paper: [AstroM<sup>3</sup>: A self-supervised multimodal model for astronomy](https://arxiv.org/abs/2411.08842)
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+ - Code Repository: [GitHub: AstroM<sup>3</sup>](https://github.com/MeriDK/AstroM3/)
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+ - Original Data: [MeriDK/AstroM3Dataset](https://huggingface.co/datasets/MeriDK/AstroM3Dataset/)
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+
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+ ## Subsets and Seeds
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+ AstroM3Dataset is available in different subset sizes:
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+
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+ - `full`: Entire dataset
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+ - `sub50`: 50% subset
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+ - `sub25`: 25% subset
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+ - `sub10`: 10% subset
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+
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+ Each subset is sampled from the respective train, validation, and test splits of the full dataset.
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+ For reproducibility, each subset is provided with different random seeds:
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+
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+ - `42`, `66`, `0`, `12`, `123`
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+
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+ ## Usage
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+ To load the dataset using the Hugging Face `datasets` library, specify the name in the format "{subset}_{seed}". For example:
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the full dataset with seed 42
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+ dataset = load_dataset("MeriDK/AstroM3Processed", name="full_42")
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+
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+ # Load the 25% subset sampled using seed 123
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+ dataset = load_dataset("MeriDK/AstroM3Processed", name="sub25_123")
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+ ```
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+
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+ ---
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+
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+ ## Citation
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+ 🤗 If you find this dataset usefull, please cite our paper 🤗
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+ ```bibtex
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+ @article{rizhko2024astrom,
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+ title={AstroM $\^{} 3$: A self-supervised multimodal model for astronomy},
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+ author={Rizhko, Mariia and Bloom, Joshua S},
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+ journal={arXiv preprint arXiv:2411.08842},
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+ year={2024}
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+ }
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+ ```
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+