Update README.md

README.md

@@ -23,10 +23,24 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: []
+         value: 0.28775471338792613
        - name: Test CER
          type: cer
-         value: []
+         value: 0.06861971204625049
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: bg
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.49783147459727384
+       - name: Test CER
+         type: cer
+         value: 0.1591062599627158
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,20 +53,16 @@ It achieves the following results on the evaluation set:
 - Loss: 0.3421
 - Wer: 0.2860
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+### Evaluation Commands
 
-## Training and evaluation data
+1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
 
-More information needed
+python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset mozilla-foundation/common_voice_8_0 --config bg --split test --log_outputs
 
-## Training procedure
+2. To evaluate on speech-recognition-community-v2/dev_data
 
+python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset speech-recognition-community-v2/dev_data --config bg --split validation --chunk_length_s 10 --stride_length_s 1
+    
 ### Training hyperparameters
 
 The following hyperparameters were used during training: