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---
configs:
- config_name: bandgap-test-filtered
data_files:
- split: fold_0
path: bandgap-test-filtered/fold_0-*
- split: fold_1
path: bandgap-test-filtered/fold_1-*
- split: fold_2
path: bandgap-test-filtered/fold_2-*
- split: fold_3
path: bandgap-test-filtered/fold_3-*
- split: fold_4
path: bandgap-test-filtered/fold_4-*
- config_name: bandgap-test-matbench
data_files:
- split: fold_0
path: bandgap-test-matbench/fold_0-*
- split: fold_1
path: bandgap-test-matbench/fold_1-*
- split: fold_2
path: bandgap-test-matbench/fold_2-*
- split: fold_3
path: bandgap-test-matbench/fold_3-*
- split: fold_4
path: bandgap-test-matbench/fold_4-*
- config_name: bandgap-train-filtered
data_files:
- split: fold_0
path: bandgap-train-filtered/fold_0-*
- split: fold_1
path: bandgap-train-filtered/fold_1-*
- split: fold_2
path: bandgap-train-filtered/fold_2-*
- split: fold_3
path: bandgap-train-filtered/fold_3-*
- split: fold_4
path: bandgap-train-filtered/fold_4-*
- config_name: bandgap-train-matbench
data_files:
- split: fold_0
path: bandgap-train-matbench/fold_0-*
- split: fold_1
path: bandgap-train-matbench/fold_1-*
- split: fold_2
path: bandgap-train-matbench/fold_2-*
- split: fold_3
path: bandgap-train-matbench/fold_3-*
- split: fold_4
path: bandgap-train-matbench/fold_4-*
- config_name: form_energy-test-filtered
data_files:
- split: fold_0
path: form_energy-test-filtered/fold_0-*
- split: fold_1
path: form_energy-test-filtered/fold_1-*
- split: fold_2
path: form_energy-test-filtered/fold_2-*
- split: fold_3
path: form_energy-test-filtered/fold_3-*
- split: fold_4
path: form_energy-test-filtered/fold_4-*
- config_name: form_energy-test-matbench
data_files:
- split: fold_0
path: form_energy-test-matbench/fold_0-*
- split: fold_1
path: form_energy-test-matbench/fold_1-*
- split: fold_2
path: form_energy-test-matbench/fold_2-*
- split: fold_3
path: form_energy-test-matbench/fold_3-*
- split: fold_4
path: form_energy-test-matbench/fold_4-*
- config_name: form_energy-train-filtered
data_files:
- split: fold_0
path: form_energy-train-filtered/fold_0-*
- split: fold_1
path: form_energy-train-filtered/fold_1-*
- split: fold_2
path: form_energy-train-filtered/fold_2-*
- split: fold_3
path: form_energy-train-filtered/fold_3-*
- split: fold_4
path: form_energy-train-filtered/fold_4-*
- config_name: form_energy-train-matbench
data_files:
- split: fold_0
path: form_energy-train-matbench/fold_0-*
- split: fold_1
path: form_energy-train-matbench/fold_1-*
- split: fold_2
path: form_energy-train-matbench/fold_2-*
- split: fold_3
path: form_energy-train-matbench/fold_3-*
- split: fold_4
path: form_energy-train-matbench/fold_4-*
- config_name: gvrh-test-filtered
data_files:
- split: fold_0
path: gvrh-test-filtered/fold_0-*
- split: fold_1
path: gvrh-test-filtered/fold_1-*
- split: fold_2
path: gvrh-test-filtered/fold_2-*
- split: fold_3
path: gvrh-test-filtered/fold_3-*
- split: fold_4
path: gvrh-test-filtered/fold_4-*
- config_name: gvrh-test-matbench
data_files:
- split: fold_0
path: gvrh-test-matbench/fold_0-*
- split: fold_1
path: gvrh-test-matbench/fold_1-*
- split: fold_2
path: gvrh-test-matbench/fold_2-*
- split: fold_3
path: gvrh-test-matbench/fold_3-*
- split: fold_4
path: gvrh-test-matbench/fold_4-*
- config_name: gvrh-train-filtered
data_files:
- split: fold_0
path: gvrh-train-filtered/fold_0-*
- split: fold_1
path: gvrh-train-filtered/fold_1-*
- split: fold_2
path: gvrh-train-filtered/fold_2-*
- split: fold_3
path: gvrh-train-filtered/fold_3-*
- split: fold_4
path: gvrh-train-filtered/fold_4-*
- config_name: gvrh-train-matbench
data_files:
- split: fold_0
path: gvrh-train-matbench/fold_0-*
- split: fold_1
path: gvrh-train-matbench/fold_1-*
- split: fold_2
path: gvrh-train-matbench/fold_2-*
- split: fold_3
path: gvrh-train-matbench/fold_3-*
- split: fold_4
path: gvrh-train-matbench/fold_4-*
- config_name: is-metal-test-classification
data_files:
- split: fold_0
path: is-metal-test-classification/fold_0-*
- split: fold_1
path: is-metal-test-classification/fold_1-*
- split: fold_2
path: is-metal-test-classification/fold_2-*
- split: fold_3
path: is-metal-test-classification/fold_3-*
- split: fold_4
path: is-metal-test-classification/fold_4-*
- config_name: is-metal-train-classification
data_files:
- split: fold_0
path: is-metal-train-classification/fold_0-*
- split: fold_1
path: is-metal-train-classification/fold_1-*
- split: fold_2
path: is-metal-train-classification/fold_2-*
- split: fold_3
path: is-metal-train-classification/fold_3-*
- split: fold_4
path: is-metal-train-classification/fold_4-*
- config_name: jdft2d-test-matbench
data_files:
- split: fold_0
path: jdft2d-test-matbench/fold_0-*
- split: fold_1
path: jdft2d-test-matbench/fold_1-*
- split: fold_2
path: jdft2d-test-matbench/fold_2-*
- split: fold_3
path: jdft2d-test-matbench/fold_3-*
- split: fold_4
path: jdft2d-test-matbench/fold_4-*
- config_name: jdft2d-train-matbench
data_files:
- split: fold_0
path: jdft2d-train-matbench/fold_0-*
- split: fold_1
path: jdft2d-train-matbench/fold_1-*
- split: fold_2
path: jdft2d-train-matbench/fold_2-*
- split: fold_3
path: jdft2d-train-matbench/fold_3-*
- split: fold_4
path: jdft2d-train-matbench/fold_4-*
- config_name: kvrh-test-filtered
data_files:
- split: fold_0
path: kvrh-test-filtered/fold_0-*
- split: fold_1
path: kvrh-test-filtered/fold_1-*
- split: fold_2
path: kvrh-test-filtered/fold_2-*
- split: fold_3
path: kvrh-test-filtered/fold_3-*
- split: fold_4
path: kvrh-test-filtered/fold_4-*
- config_name: kvrh-test-matbench
data_files:
- split: fold_0
path: kvrh-test-matbench/fold_0-*
- split: fold_1
path: kvrh-test-matbench/fold_1-*
- split: fold_2
path: kvrh-test-matbench/fold_2-*
- split: fold_3
path: kvrh-test-matbench/fold_3-*
- split: fold_4
path: kvrh-test-matbench/fold_4-*
- config_name: kvrh-train-filtered
data_files:
- split: fold_0
path: kvrh-train-filtered/fold_0-*
- split: fold_1
path: kvrh-train-filtered/fold_1-*
- split: fold_2
path: kvrh-train-filtered/fold_2-*
- split: fold_3
path: kvrh-train-filtered/fold_3-*
- split: fold_4
path: kvrh-train-filtered/fold_4-*
- config_name: kvrh-train-matbench
data_files:
- split: fold_0
path: kvrh-train-matbench/fold_0-*
- split: fold_1
path: kvrh-train-matbench/fold_1-*
- split: fold_2
path: kvrh-train-matbench/fold_2-*
- split: fold_3
path: kvrh-train-matbench/fold_3-*
- split: fold_4
path: kvrh-train-matbench/fold_4-*
- config_name: perovskites-test-filtered
data_files:
- split: fold_0
path: perovskites-test-filtered/fold_0-*
- split: fold_1
path: perovskites-test-filtered/fold_1-*
- split: fold_2
path: perovskites-test-filtered/fold_2-*
- split: fold_3
path: perovskites-test-filtered/fold_3-*
- split: fold_4
path: perovskites-test-filtered/fold_4-*
- config_name: perovskites-test-matbench
data_files:
- split: fold_0
path: perovskites-test-matbench/fold_0-*
- split: fold_1
path: perovskites-test-matbench/fold_1-*
- split: fold_2
path: perovskites-test-matbench/fold_2-*
- split: fold_3
path: perovskites-test-matbench/fold_3-*
- split: fold_4
path: perovskites-test-matbench/fold_4-*
- config_name: perovskites-train-filtered
data_files:
- split: fold_0
path: perovskites-train-filtered/fold_0-*
- split: fold_1
path: perovskites-train-filtered/fold_1-*
- split: fold_2
path: perovskites-train-filtered/fold_2-*
- split: fold_3
path: perovskites-train-filtered/fold_3-*
- split: fold_4
path: perovskites-train-filtered/fold_4-*
- config_name: perovskites-train-matbench
data_files:
- split: fold_0
path: perovskites-train-matbench/fold_0-*
- split: fold_1
path: perovskites-train-matbench/fold_1-*
- split: fold_2
path: perovskites-train-matbench/fold_2-*
- split: fold_3
path: perovskites-train-matbench/fold_3-*
- split: fold_4
path: perovskites-train-matbench/fold_4-*
- config_name: phonons-test-matbench
data_files:
- split: fold_0
path: phonons-test-matbench/fold_0-*
- split: fold_1
path: phonons-test-matbench/fold_1-*
- split: fold_2
path: phonons-test-matbench/fold_2-*
- split: fold_3
path: phonons-test-matbench/fold_3-*
- split: fold_4
path: phonons-test-matbench/fold_4-*
- config_name: phonons-train-matbench
data_files:
- split: fold_0
path: phonons-train-matbench/fold_0-*
- split: fold_1
path: phonons-train-matbench/fold_1-*
- split: fold_2
path: phonons-train-matbench/fold_2-*
- split: fold_3
path: phonons-train-matbench/fold_3-*
- split: fold_4
path: phonons-train-matbench/fold_4-*
- config_name: pretrain100k
data_files:
- split: train
path: data/pretrain100k-*
- split: test
path: data/test-*
- config_name: pretrain2m
data_files:
- split: train
path: data/pretrain2m-*
- split: test
path: data/test-*
- config_name: pretrain300k
data_files:
- split: train
path: data/pretrain300k-*
- split: test
path: data/test-*
- config_name: pretrain30k
data_files:
- split: train
path: data/pretrain30k-*
- split: test
path: data/test-*
dataset_info:
- config_name: bandgap-test-filtered
features:
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dtype: string
- name: atom_sequences
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- name: cif_symmetrized
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- name: slices
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- name: crystal_text_llm
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- name: mbid
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- name: local_env
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- name: fold_3
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num_examples: 21222
- name: fold_4
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num_examples: 21222
download_size: 223645904
dataset_size: 644437106
- config_name: bandgap-test-matbench
features:
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- name: crystal_text_llm
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- name: fold_4
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num_examples: 21222
download_size: 223645868
dataset_size: 644437106
- config_name: bandgap-train-filtered
features:
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dataset_size: 953232453
- config_name: bandgap-train-matbench
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dataset_size: 2581141969
- config_name: default
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- config_name: form_energy-test-filtered
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- config_name: form_energy-test-matbench
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- config_name: form_energy-train-filtered
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---
# Dataset Card for MatText
## Table of Contents
- [Dataset Card for MatText](#dataset-card-for-mattext)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
- [Who are the source language producers?](#who-are-the-source-language-producers)
- [Annotations](#annotations)
- [Annotation process](#annotation-process)
- [Who are the annotators?](#who-are-the-annotators)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://github.com/lamalab-org/MatText
- **Repository:** https://github.com/lamalab-org/MatText
- **Paper:** https://arxiv.org/abs/2406.17295
- **Leaderboard:** To be published
- **Point of Contact:** [Nawaf Alampara](https://github.com/n0w0f)
### Dataset Summary
The dataset contains crystal structures in various text representations and labels for some subsets.
### Supported Tasks and Leaderboards
The task for the pertaining dataset is self-supervised language modeling. For the fine-tuning dataset, supervised property prediction.
### Languages
This is not a natural language dataset.
## Dataset Structure
### Data Instances
The instances represent materials. They are crystal structures of 3D-connected solid materials.
### Data Fields
- `local_env` (string): The Local Env text representation of a material
- `slices` (string): The [SLICES representation](https://github.com/xiaohang007/SLICES) of a material
- `cif_p1` (string): The CIF representation of a material in P$_1$ symmetry
- `composition` (string): The composition of a material in Hill notation
- `crystal_text_llm` (string): The text representation of a material proposed in [Gruver et al.](https://arxiv.org/abs/2402.04379)
- `atom_sequences_plusplus` (string): A space-separated enumeration of element symbols and the lattice parameters
- `labels` (float): For the `gvrh` datasets, the targets are the base 10 logarithm of the DFT Voigt-Reuss-Hill average shear moduli in GPa. For the `kvrh` datasets, the base 10 logarithm of the DFT Voigt-Reuss-Hill average bulk moduli in GPa. For the `perovskite` dataset, the labels are the heat of formation of the entire cell, in eV, as calculated by RPBE GGA-DFT. For the pretaining datasets, there are no labels.
- `mbid` (string): a unique identifier of a material
- `cif_symmetrized` (string): The CIF representation of a material in higher symmetry
- `atom_sequences` (string): A space-separated enumeration of element symbols
- `zmatrix` (string): A z-matrix (internal coordinates) representation of the material
### Data Splits
For the benchmarking we follow the five-fold cross-validation proposed by MatBench. The folds are uploaded as splits to HuggingFace.
## Dataset Creation
### Curation Rationale
The dataset was created to enable the training and benchmarking of text-based modeling of materials properties. However, how different representations perform for materials modeling tasks has not been understood.
### Source Data
#### Initial Data Collection and Normalization
The pertaining dataset is a subset of the materials deposited in the NOMAD archive. We queried only 3D-connected structures (i.e., excluding 2D materials, which often require special treatment) and, for consistency, limited our query to materials for which the bandgap has been computed using the PBE functional and the VASP code.
The benchmarking datasets are derived from MatBench. We limited ourselves to the smaller subsets for regression tasks, for which crystal structures are provided. Some instances are dropped because text representations could not be derived.
#### Who are the source language producers?
n/a
### Annotations
#### Annotation process
The only annotations are text representations that we derived using our MatText framework.
#### Who are the annotators?
n/a
### Personal and Sensitive Information
n/a
## Considerations for Using the Data
### Social Impact of Dataset
There are many potential consequences of our work, none of which we feel are societal impacts that must be specifically highlighted here.
### Discussion of Biases
There might be biases in certain parts of the materials space being oversampled.
### Other Known Limitations
To our knowledge, there are no duplicates. While we took care to avoid errors, there might be errors, for example, due to problems with the crystal structures in the raw data.
## Additional Information
### Dataset Curators
The dataset was curated by Nawaf Alampara, Santiago Miret, and Kevin Maik Jablonka.
### Licensing Information
The dataset is provided with an MIT license.
### Citation Information
If you found the dataset useful, please cite:
```
@misc{alampara2024mattextlanguagemodelsneed,
title={MatText: Do Language Models Need More than Text & Scale for Materials Modeling?},
author={Nawaf Alampara and Santiago Miret and Kevin Maik Jablonka},
year={2024},
eprint={2406.17295},
archivePrefix={arXiv},
primaryClass={cond-mat.mtrl-sci}
url={https://arxiv.org/abs/2406.17295},
}
```
### Contributions
Thanks to [n0w0f](https://github.com/n0w0f) for adding this dataset.