PROJECT_NAME = 'Kaggle_Readability'
EXPERIMENT_NAME = 'Experiment_Roberta'
SEED = 42
EPOCHS = 12
PRETRAINED = 'roberta-base'
MAX_LENGTH = 64
COLUMNS_ENCODE = ['product_name','ingredients_text','brands_tags','additives']
BATCH_SIZE = 64
NUM_WORKERS = 72
DEVICE = 'cpu'
LOSS_NAME = 'MSE'
OPTIMIZER_NAME = 'AdamW'
LEARNING_RATE = 4e-05
SCHEDULER_NAME = 'linear_with_warmup'
EARLY_STOPPING = 5
MODE = 'min'
MODE_SCHEDULER = 'on_batch'
WEIGHT_DECAY = 0.01
DROPOUT = 0.1
WARMUP_RATIO = 0.1
SCHEDULER_PARAMETERS = {'WARMUP_RATIO': WARMUP_RATIO}

PROJECT_NAME = 'Kaggle_Readability'
EXPERIMENT_NAME = 'Experiment_Roberta'
SEED = 42
EPOCHS = 12
PRETRAINED = 'roberta-base'
MAX_LENGTH = 64
COLUMNS_ENCODE = ['product_name','ingredients_text','brands_tags','additives']
BATCH_SIZE = 64
NUM_WORKERS = 72
DEVICE = 'cpu'
LOSS_NAME = 'MSE'
OPTIMIZER_NAME = 'AdamW'
LEARNING_RATE = 4e-05
SCHEDULER_NAME = 'linear_with_warmup'
EARLY_STOPPING = 5
MODE = 'min'
MODE_SCHEDULER = 'on_batch'
WEIGHT_DECAY = 0.01
DROPOUT = 0.1
WARMUP_RATIO = 0.1
SCHEDULER_PARAMETERS = {'WARMUP_RATIO': WARMUP_RATIO}
