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Co-authored-by: Heloise Chomet <heloise-chomet@users.noreply.huggingface.co>

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  # Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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  {}
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  ---
 
 
 
 
 
 
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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 1 737 896 structures and the validation set 87 922 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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  ## Version 2 SPICE dataset source
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  https://pubs.acs.org/doi/10.1021/acs.jctc.4c00794
 
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  # Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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  {}
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  ---
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+
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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