Update README.md

README.md

@@ -40,7 +40,7 @@ text = pipe("audio_path.wav")["text"]
 print(text)
 ```
 
-## Evaluation Performance
+<!-- ## Evaluation Performance
 WER calculated with newmm tokenizer for Thai word segmentation.
 | Model                                   |       CV18 (WER)       |        Gowejee (WER)      |     LOTUS-TRD (WER)    |      Thai Dialect (WER)    |        Elderly (WER)       |     Gigaspeech2 (WER)      |       Fleurs (WER)         |     Distant Meeting (WER)  |       Podcast (WER)        |
 |:----------------------------------------|:----------------------:|:-------------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|
@@ -50,7 +50,7 @@ WER calculated with newmm tokenizer for Thai word segmentation.
 | monsoon-whisper-medium-gigaspeech2      |         11.66          |          20.50            |         41.04          |           42.06            |           7.57             |           21.40            |           21.54            |           51.65            |           38.89            |
 | pathumma-whisper-th-large-v3            |         8.68           |           9.84            |         15.47          |           19.85            |           1.53             |           21.66            |           15.65            |           51.56            |           36.47            |
 
-**Note:** Other models not target fine-tuned on dialect datasets may be less representative of dialect performance.
+**Note:** Other models not target fine-tuned on dialect datasets may be less representative of dialect performance. -->
 
 ## Limitations and Future Work
 Additional information is needed