Update README.md

README.md

@@ -64,9 +64,9 @@ tensorboard --logdir callback_path
 
 ## LibriSpeech Performance
 
-Model / Test Dataset                    Gigaspeech_test              VLSP2023_pb_test             VLSP2023_pr_test
-                              (greedy/n-gram beam search)  (greedy/n-gram beam search)  (greedy/n-gram beam search)
-Efficient-Conformer-Small-CTC        19.61/21.11                  23.06/21.11                  23.17/21.42
+| Model                          | Gigaspeech_test (greedy/n-gram beam search) | VLSP2023_pb_test (greedy/n-gram beam search) | VLSP2023_pr_test (greedy/n-gram beam search) |
+|---------------------------------|--------------------------------------------|----------------------------------------------|----------------------------------------------|
+| Efficient-Conformer-Small-CTC   | 19.61 / 21.11                              | 23.06 / 21.11                                | 23.17 / 21.42                                |
 
 In the competition organized by VLSP, I used the Efficient Conformer Large architecture with approximately 127 million parameters. You can find the detailed results in the technical report below:
 https://www.overleaf.com/read/nhqjtcpktjyc#3b472e