Update README.md

README.md

@@ -23,12 +23,12 @@ from transformers import BertForSequenceClassification, BertTokenizer, TextClass
 model_path = "JiaqiLee/robust-bert-yelp"
 tokenizer = BertTokenizer.from_pretrained(model_path)
 model = BertForSequenceClassification.from_pretrained(model_path, num_labels=2)
-pipeline =  TextClassificationPipeline(model=model, tokenizer=tokenizer)
+pipeline = TextClassificationPipeline(model=model, tokenizer=tokenizer)
 print(pipeline("Definitely a greasy spoon! Always packed here and always a wait but worth it."))
 ```
 
 ## Training data
-The training data comes Huggingface [yelp polarity dataset](https://huggingface.co/datasets/yelp_polarity). We use 90% of the `train.csv` data to train the model. \
+The training data comes from Huggingface [yelp polarity dataset](https://huggingface.co/datasets/yelp_polarity). We use 90% of the `train.csv` data to train the model. \
 We augment original training data with adversarial examples generated by PWWS, TextBugger and TextFooler.
 
 ## Evaluation results