from transformers import BertTokenizer, BertModel

MAX_LENGTH = 128
TOKENIZER = BertTokenizer.from_pretrained("bert-base-uncased")
TRAIN_BATCH_SIZE = 8
VALID_BATCH_SIZE = 4
MODEL = BertModel.from_pretrained("bert-base-uncased")
NUM_EPOCHS = 2
MODEL_PATH = "/"

969e2e97b9e538d7496fb259a07de8dab529b317
<mask token>

<mask token>
MAX_LENGTH = 128
TOKENIZER = BertTokenizer.from_pretrained('bert-base-uncased')
TRAIN_BATCH_SIZE = 8
VALID_BATCH_SIZE = 4
MODEL = BertModel.from_pretrained('bert-base-uncased')
NUM_EPOCHS = 2
MODEL_PATH = '/'

from transformers import BertTokenizer, BertModel
MAX_LENGTH = 128
TOKENIZER = BertTokenizer.from_pretrained('bert-base-uncased')
TRAIN_BATCH_SIZE = 8
VALID_BATCH_SIZE = 4
MODEL = BertModel.from_pretrained('bert-base-uncased')
NUM_EPOCHS = 2
MODEL_PATH = '/'

from transformers import BertTokenizer, BertModel

MAX_LENGTH = 128
TOKENIZER = BertTokenizer.from_pretrained("bert-base-uncased")
TRAIN_BATCH_SIZE = 8
VALID_BATCH_SIZE = 4
MODEL = BertModel.from_pretrained("bert-base-uncased")
NUM_EPOCHS = 2
MODEL_PATH = "/"
