7681e0305184eaf164069485003ab8c6e3e5e155,scripts/bert/finetune_classifier.py,,,#,48

Before Change

data_train = MRPCDataset("train").transform(trans)
data_dev = MRPCDataset("dev").transform(trans)

bert_dataloader = mx.gluon.data.DataLoader(data_train, batch_size=batch_size,
                                           shuffle=True, last_batch="rollover")
bert_dataloader_dev = mx.gluon.data.DataLoader(data_dev, batch_size=test_batch_size,
                                               shuffle=False)

def evaluate():

After Change

lr = args.lr
accumulate = args.accumulate
log_interval = args.log_interval * accumulate if accumulate else args.log_interval
if accumulate:
    logging.info("Using gradient accumulation. Effective batch size = %d"%(accumulate*batch_size))

// random seed
np.random.seed(args.seed)
random.seed(args.seed)
mx.random.seed(args.seed)

Instances