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

Before Change

metric = mx.metric.Accuracy()

trans = ClassificationTransform(tokenizer, MRPCDataset.get_labels(), args.max_len)
data_train = MRPCDataset("train").transform(trans)
data_dev = MRPCDataset("dev").transform(trans)

bert_dataloader = mx.gluon.data.DataLoader(data_train, batch_size=batch_size,

After Change

dev_batch_size = args.dev_batch_size
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

Instances