Update README.md

README.md

@@ -15,7 +15,7 @@ Please check the [official repository](https://github.com/microsoft/DeBERTa) for
 
 In DeBERTa V3, we replaced the MLM objective with the RTD(Replaced Token Detection) objective introduced by ELECTRA for pre-training, as well as some innovations to be introduced in our upcoming paper. Compared to DeBERTa-V2,  our V3 version significantly improves the model performance in downstream tasks.  You can find a simple introduction about the model from the appendix A11 in our original [paper](https://arxiv.org/abs/2006.03654),  but we will provide more details in a separate write-up.
 
-The DeBERTa V3 large model comes with 12 layers and a hidden size of 768. Its total parameter number is 183M since we use a vocabulary containing 128K tokens which introduce 98M parameters in the Embedding layer.  This model was trained using the 160GB data as DeBERTa V2.
+The DeBERTa V3 base model comes with 12 layers and a hidden size of 768. Its total parameter number is 183M since we use a vocabulary containing 128K tokens which introduce 98M parameters in the Embedding layer.  This model was trained using the 160GB data as DeBERTa V2.
 
 
 #### Fine-tuning on NLU tasks