| NUM_EPOCHS = 8 #Number of epochs to train for | |
| BATCH_SIZE = 18 #Change this depending on GPU memory | |
| NUM_WORKERS = 4 #A value of 0 means the main process loads the data | |
| LEARNING_RATE = 2e-5 | |
| LOG_EVERY = 200 #iterations after which to log status during training | |
| VALID_NITER = 2000 #iterations after which to evaluate model and possibly save (if dev performance is a new max) | |
| PRETRAIN_PATH = None #path to pretrained model, such as BlueBERT or BioBERT | |
| PAD_IDX = 0 #padding index as required by the tokenizer | |
| #CONDITIONS is a list of all 14 medical observations | |
| CONDITIONS = ['Enlarged Cardiomediastinum', 'Cardiomegaly', 'Lung Opacity', | |
| 'Lung Lesion', 'Edema', 'Consolidation', 'Pneumonia', 'Atelectasis', | |
| 'Pneumothorax', 'Pleural Effusion', 'Pleural Other', 'Fracture', | |
| 'Support Devices', 'No Finding'] | |
| CLASS_MAPPING = {0: "Blank", 1: "Positive", 2: "Negative", 3: "Uncertain"} | |