Model for mbjdiel_dielectric¶
- Description: This is a benchmark to evaluate how accurately an AI model can predict the frequency-dependent dielectric function computed with the TBmBJ meta-GGA functional using the JARVIS-DFT (dft_3d) dataset. The dataset contains different types of chemical formula and atomic structures. Here we use multi-mean absolute error (multi-MAE) to compare models with respect to DFT accuracy.
Reference(s): https://github.com/atomgptlab/jarvis_leaderboard, https://www.nature.com/articles/s41524-020-00440-1, https://github.com/atomgptlab/alignn
Model benchmarks
| Model name | Dataset | MAE | Team name | Dataset size | Date submitted | Notes |
|---|---|---|---|---|---|---|
| alignn2_radius | mbjdiel | 0.0005285534747760491 | AtomGPTLab | 7056 | 07-30-2026 | CSV, JSON, run.sh, Info |
| baseline_mean | mbjdiel | 0.0018214565912305512 | AtomGPTLab | 7056 | 07-31-2026 | CSV, JSON, run.sh, Info |
| alignn2_knn | mbjdiel | 0.0005194313861386138 | AtomGPTLab | 7056 | 07-30-2026 | CSV, JSON, run.sh, Info |