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# Update |
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As of the mlip v0.1.2 release, the SPICE2 curated dataset was also updated. |
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The main reason the removal of a small number of structures that led to unusually high energy errors with our models. |
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We also wanted to remove structures with Li, K and Na atomis, as these elements were absent from the validation set. |
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0.2 % of the training set and validation set was removed. Details added to the filtering process below. |
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# SPICE2_curated |
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The provided dataset is based on the version 2 SPICE dataset. The SPICE dataset was chosen for its diversity, both in chemical and conformational space, |
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compromising of approximately 2 million structures computed at the ωB97M-D3(BJ)/def2-TZVPPD level of theory. |
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## Dataset Structure |
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The provided dataset is split into a training set and a validation set with a 95/5 split. The split was done per molecular |
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SMILES, insuring that different conformations of the same molecule do not appear in both the training and |
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validation set. The training set contains 1 734 158 structures and the validation set 87 764 structures. |
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## Filtering Process |
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The version 2 SPICE dataset was filtered by removing the following structures: |
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- **Unphysical structures:** Only keeping structures where all hydrogen atoms have exactly one bond (removing 42 689 structures). |
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- **Charged systems:** Removing all charged systems (removing 142 647 structures). |
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- **High forces:** Applying a total force filter of 0.1 eV/A and a maximum force filter of 15 eV/A (removing 1 024 structures). |
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- **High energy errors:** Removing structures with high z-score when computing energy errors with our three trained models (removing 3656 structures from training and 158 from validation). |
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- **Atomic species** Removing any structures containing Li, K or Na (removing 82 structures) |
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## Version 2 SPICE dataset source |
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https://pubs.acs.org/doi/10.1021/acs.jctc.4c00794 |
