Update README.md

README.md

@@ -93,10 +93,10 @@ It achieves the following results on the evaluation set:
 - Loss: 0.1344
 - Wer: 6.3465
 
-Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the test sets (WER):
+Using the [evaluation script](https://github.com/huggingface/community-events/blob/main/whisper-fine-tuning-event/run_eval_whisper_streaming.py) provided in the Whisper Sprint the model achieves these results on the test sets (WER):
 
 - **google/fleurs: 4.0266 %**  
-(python [run_eval_whisper_streaming.py](https://github.com/huggingface/community-events/blob/main/whisper-fine-tuning-event/run_eval_whisper_streaming.py) --model_id="deepdml/whisper-medium-mix-es" --dataset="google/fleurs" --config="es_419" --device=0 --language="es")
+(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-es" --dataset="google/fleurs" --config="es_419" --device=0 --language="es")
 
 - **facebook/multilingual_librispeech: 4.6644 %**  
 (python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-es" --dataset="facebook/multilingual_librispeech" --config="spanish" --device=0 --language="es")
@@ -121,7 +121,8 @@ Training data used:
 - **facebook/multilingual_librispeech:** spanish, train
 - **facebook/voxpopuli:** es, train
 
-Evaluating over test split from above datasets.
+Evaluating over test split from mozilla-foundation/common_voice_11_0 datasets
+
 ## Training procedure
 
 ### Training hyperparameters