# config.yaml
seed: 2102
device: cuda
train_batch_size: 256
learning_rate: 0.001
num_epochs: 60
scheduler_patience: 5
scheduler_factor: 0.2
train_split: 0.9
dataset_path: 'data/prottrans_molformer_tensor_dataset100k.json'
model_train_save_path: 'data/BAPULM_weights.pth'
model_inference_path: 'data/BAPULM_results_molformer_reproduce_json.pth'
inference_batch_size: 64
benchmark_files:
  - 'data/benchmark1k2101.csv'
  - 'data/Test2016_290.csv'
  - 'data/CSAR-HiQ_36.csv'