Update README.md

README.md

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 # Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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+# Update
+As of the mlip v0.1.2 release, the SPICE2 curated dataset was also updated.
+The main reason the removal of a small number of structures that led to unusually high energy errors with our models.
+We also wanted to remove structures with Li, K and Na atomis, as these elements were absent from the validation set.
+0.2 % of the training set and validation set was removed. Details added to the filtering process below.
 # SPICE2_curated
 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,
 compromising of approximately 2 million structures computed at the ωB97M-D3(BJ)/def2-TZVPPD level of theory.
 ## Dataset Structure
 The provided dataset is split into a training set and a validation set with a 95/5 split. The split was done per molecular
 SMILES, insuring that different conformations of the same molecule do not appear in both the training and
-validation set. The training set contains 1 737 896 structures and the validation set  87 922 structures.
+validation set. The training set contains 1 734 158 structures and the validation set  87 764 structures.
 ## Filtering Process
 The version 2 SPICE dataset was filtered by removing the following structures:
 - **Unphysical structures:** Only keeping structures where all hydrogen atoms have exactly one bond (removing 42 689 structures). 
 - **Charged systems:** Removing all charged systems (removing 142 647 structures).
 - **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).
+- **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).
+- **Atomic species** Removing any structures containing Li, K or Na (removing 82 structures)
 ## Version 2 SPICE dataset source
 https://pubs.acs.org/doi/10.1021/acs.jctc.4c00794