Update README.md

README.md

@@ -28,6 +28,20 @@ model-index:
        - name: Test CER
          type: cer
          value: 0.1102657634184471
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: bas
+    metrics:
+       - name: Test WER
+         type: wer
+         value: NA
+       - name: Test CER
+         type: cer
+         value: NA
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,19 +54,15 @@ It achieves the following results on the evaluation set:
 - Loss: 0.5997
 - Wer: 0.3870
 
-## Model description
-
-More information needed
+### Evaluation Commands
 
-## Intended uses & limitations
+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-bas-v1 --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs
 
-## Training and evaluation data
+2. To evaluate on speech-recognition-community-v2/dev_data
 
-More information needed
-
-## Training procedure
+Basaa (bas) language isn't available in speech-recognition-community-v2/dev_data
 
 ### Training hyperparameters
 
@@ -100,9 +110,3 @@ The following hyperparameters were used during training:
 - Pytorch 1.10.0+cu111
 - Datasets 1.18.2
 - Tokenizers 0.11.0
-
-### Evaluation Script
-
-!python eval.py \
-    --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1 \
-    --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs