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  # Description
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  This is an [OMatG (Open Materials Generation)](https://github.com/FERMat-ML/OMatG) model for crystal structure prediction
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  (CSP) of inorganic crystals trained on the MPTS-52 (Materials Project Time Splits) dataset.
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-
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- This dataset is also included in OMatG.
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  The subdirectories in this repository contain various model hyperparameters and training checkpoints for a
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  variety of MTPS-52-CSP models.
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  # Recommendations
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  The [Linear-ODE checkpoints](https://huggingface.co/OMatG/MPTS-52-CSP/tree/main/Linear-ODE)
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- currently provide the best results with respect to structure stability, novelty, and uniqueness.
 
 
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  # Citation
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  Please cite [our paper on OpenReview](https://openreview.net/forum?id=gHGrzxFujU) if using OMatG.
 
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  # Description
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  This is an [OMatG (Open Materials Generation)](https://github.com/FERMat-ML/OMatG) model for crystal structure prediction
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  (CSP) of inorganic crystals trained on the MPTS-52 (Materials Project Time Splits) dataset.
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+
 
 
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  The subdirectories in this repository contain various model hyperparameters and training checkpoints for a
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  variety of MTPS-52-CSP models.
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  # Recommendations
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  The [Linear-ODE checkpoints](https://huggingface.co/OMatG/MPTS-52-CSP/tree/main/Linear-ODE)
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+ currently provide the best results with respect to the match rate.
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+
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+ The [VE-SBD checkpoints](https://huggingface.co/OMatG/MPTS-52-CSP/tree/main/VESBD-ODE) currently provide the best results with respect to average root-mean square distance between generated and matched reference structures.
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  # Citation
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  Please cite [our paper on OpenReview](https://openreview.net/forum?id=gHGrzxFujU) if using OMatG.