Update simple_demo.py

demo/text-classification/simple_demo.py

-#coding:utf-8
 import paddle.fluid as fluid
 import paddlehub as hub
 
-# Load ERNIE pretrained model
 module = hub.Module(name="ernie")
 inputs, outputs, program = module.context(trainable=True, max_seq_len=128)
 
-# Create ClassifyReader
 reader = hub.reader.ClassifyReader(
     hub.dataset.ChnSentiCorp(), module.get_vocab_path(), max_seq_len=128)
 
-# Create Text Classification Task
 task = hub.create_text_cls_task(feature=outputs["pooled_output"], num_classes=2)
 
-# Configure Fine-tune strategy
 strategy = hub.AdamWeightDecayStrategy(learning_rate=5e-5)
 
-# Setting runing config
 config = hub.RunConfig(
     use_cuda=True, num_epoch=3, batch_size=32, strategy=strategy)
+
 feed_list = [
     inputs["input_ids"].name, inputs["position_ids"].name,
     inputs["segment_ids"].name, inputs["input_mask"].name,
     task.variable("label").name
 ]
 
-# Start fine-tuning
 hub.finetune_and_eval(task, reader, feed_list, config)