Update README.md

README.md

@@ -8,9 +8,32 @@ language:
 metrics:
 - exact_match
 - f1
+
+model-index:
+- name: VMware/TinyRoBERTa-MRQA
+  results:
+  - task:
+      type: Extractive Question-Answering            
+    dataset:
+      type: mrqa       # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: mrqa       # Required. A pretty name for the dataset. Example: Common Voice (French)
+
+    metrics:
+      - type: exact_match       # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 69.38       # Required. Example: 20.90
+        name: Eval EM         # Optional. Example: Test WER
+      - type: f1         # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 80.07      # Required. Example: 20.90
+        name: Eval F1         # Optional. Example: Test WER
+      - type: exact_match         # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 53.29       # Required. Example: 20.90
+        name: Test EM         # Optional. Example: Test WER
+      - type: f1        # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 64.16      # Required. Example: 20.90
+        name: Test F1         # Optional. Example: Test WER
 ---
 
-# tinyroberta-mrqa
+# TinyRoBERTa-MRQA
 
 This is the *distilled* version of the [VMware/roberta-large-mrqa](https://huggingface.co/VMware/roberta-large-mrqa) model. This model has a comparable prediction quality to the base model and runs twice as fast.