Update README.md

README.md

@@ -28,6 +28,33 @@ model-index:
        - name: Test CER
          type: cer
          value: 0.051648321634392154
+       - name: Test WER (+LM)
+         type: wer
+         value: 0.13482652613087395
+       - name: Test CER (+LM)
+         type: cer
+         value: 0.038838663862562475
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: sl
+    metrics:
+       - name: Dev WER
+         type: wer
+         value: 0.5406156320830592
+       - name: Dev CER
+         type: cer
+         value: 0.22249723590310583
+       - name: Dev WER (+LM)
+         type: wer
+         value: 
+       - name: Dev CER (+LM)
+         type: cer
+         value: 
+
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,19 +67,15 @@ It achieves the following results on the evaluation set:
 - Loss: 0.2756
 - Wer: 0.2279
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
+### Evaluation Commands
 
-More information needed
+1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
 
-## Training and evaluation data
+python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 --dataset mozilla-foundation/common_voice_8_0 --config sl --split test --log_outputs
 
-More information needed
+2. To evaluate on speech-recognition-community-v2/dev_data
 
-## Training procedure
+python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 --dataset speech-recognition-community-v2/dev_data --config sl --split validation --chunk_length_s 10 --stride_length_s 1
 
 ### Training hyperparameters