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| chemprop_dir=../../../chemprop # location of chemprop directory, CHANGE ME | |
| results_dir=results_qm9_gap | |
| train_path=../data/qm9/train.csv | |
| val_path=../data/qm9/val.csv | |
| test_path=../data/qm9/test.csv | |
| #Hyperparameter optimization | |
| python $chemprop_dir/hyperparameter_optimization.py \ | |
| --dataset_type regression \ | |
| --data_path $train_path \ | |
| --separate_val_path $val_path \ | |
| --separate_test_path $val_path \ | |
| --num_iters 30 \ | |
| --epochs 50 \ | |
| --aggregation norm \ | |
| --search_parameter_keywords depth ffn_num_layers hidden_size ffn_hidden_size dropout \ | |
| --config_save_path $results_dir/config.json \ | |
| --hyperopt_checkpoint_dir $results_dir \ | |
| --log_dir $results_dir \ | |
| --target_columns gap | |
| #Training with optimized hyperparameters | |
| python $chemprop_dir/train.py \ | |
| --dataset_type regression \ | |
| --data_path $train_path \ | |
| --separate_val_path $val_path \ | |
| --separate_test_path $test_path \ | |
| --epochs 50 \ | |
| --aggregation norm \ | |
| --config_path $results_dir/config.json \ | |
| --save_dir $results_dir \ | |
| --ensemble_size 5 \ | |
| --save_preds \ | |
| --extra_metrics mae \ | |
| --show_individual_scores \ | |
| --target_columns gap | |