Update README.md

README.md

@@ -172,7 +172,8 @@ The following table contains test results on the HuggingFace model in comparison
 | RTE   | Accuracy               | [67.15](https://huggingface.co/gchhablani/bert-base-cased-finetuned-qnli)       | [62.82](https://huggingface.co/gchhablani/fnet-base-finetuned-qnli)       | 04:51         | 03:24    |
 | WNLI  | Accuracy               | [46.48](https://huggingface.co/gchhablani/bert-base-cased-finetuned-wnli)       | [54.93](https://huggingface.co/gchhablani/fnet-base-finetuned-wnli)       | 03:23         | 02:37    |
 
-We can see that the FNet model achieves around ~93% of BERT's performance on average and takes around ~70% time to fine-tune on the downstream tasks.
+We can see that the FNet model achieves around ~93% of BERT's performance on average while it requires on average ~30% less time to fine-tune on the downstream tasks.
+
 ### BibTeX entry and citation info
 
 ```bibtex