The train_emulators.py script will train emulators and create this report.
This is the data from training of the reizman suzuki benchmark for 1000 epochs with 5 cross-validation folds.
| case | avg_fit_time | avg_val_r2 | avg_val_RMSE | avg_test_r2 | avg_test_RMSE |
|---|---|---|---|---|---|
| case_1 | 3.52 | 0.81 | 11.21 | 0.93 | 7.66 |
| case_2 | 3.58 | 0.59 | 5.54 | 0.67 | 4.91 |
| case_3 | 3.61 | 0.76 | 13.11 | 0.84 | 12.04 |
| case_4 | 3.6 | 0.7 | 15.99 | 0.74 | 13.8 |
This is the data from training of the Baumgartner C-N aniline cross-coupling benchmark for 1000 epochs with 5 cross-validation folds.
| case | avg_fit_time | avg_val_r2 | avg_val_RMSE | avg_test_r2 | avg_test_RMSE |
|---|---|---|---|---|---|
| one-hot | 3.54 | 0.79 | 0.18 | 0.88 | 0.13 |
| descriptors | 3.52 | 0.84 | 0.16 | 0.9 | 0.12 |