Update README.md

README.md

@@ -32,11 +32,11 @@ There are three versions of models released. The details are:
 |   [zero-shot-classify-SSTuning-large](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-large)    |    [roberta-large](https://huggingface.co/roberta-large)      | 355M     |   Medium   | Medium | 5.12M |
 |   [zero-shot-classify-SSTuning-ALBERT](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-ALBERT)   |  [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2)      |  235M   |    High  | Low| 5.12M |
 
-
+Please note that zero-shot-classify-SSTuning-base is trained with more data (20.48M) than the paper, as this will increase the accuracy.
 
 
 ## Intended uses & limitations
-The model can be used for zero-shot text classification such sentiment analysis and topic classificaion. No further finetuning is needed.
+The model can be used for zero-shot text classification such as sentiment analysis and topic classification. No further finetuning is needed.
 
 The number of labels should be 2 ~ 20.