Update README.md

README.md

@@ -11,6 +11,39 @@ tags:
 - deberta-v3
 - mdeberta
 - question-answering
+model-index:
+- name: sjrhuschlee/mdeberta-v3-base-squad2
+  results:
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad_v2
+      type: squad_v2
+      config: squad_v2
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 80.3841
+      name: Exact Match
+    - type: f1
+      value: 83.8713
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad
+      type: squad
+      config: plain_text
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 83.7843
+      name: Exact Match
+    - type: f1
+      value: 90.9635
+      name: F1
 ---
 
 # mdeberta-v3-base for QA
@@ -41,4 +74,38 @@ res = nlp(qa_input)
 # b) Load model & tokenizer
 model = AutoModelForQuestionAnswering.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
+```
+
+### Metrics
+```bash
+# Squad v2
+{
+    "eval_HasAns_exact": 77.7327935222672,
+    "eval_HasAns_f1": 84.7172608568916,
+    "eval_HasAns_total": 5928,
+    "eval_NoAns_exact": 83.02775441547519,
+    "eval_NoAns_f1": 83.02775441547519,
+    "eval_NoAns_total": 5945,
+    "eval_best_exact": 80.38406468457846,
+    "eval_best_exact_thresh": 0.0,
+    "eval_best_f1": 83.87129810154576,
+    "eval_best_f1_thresh": 0.0,
+    "eval_exact": 80.38406468457846,
+    "eval_f1": 83.87129810154582,
+    "eval_runtime": 221.4855,
+    "eval_samples": 12054,
+    "eval_samples_per_second": 54.423,
+    "eval_steps_per_second": 2.271,
+    "eval_total": 11873
+}
+
+# Squad
+{
+    "eval_exact_match": 83.78429517502366,
+    "eval_f1": 90.96354972948996,
+    "eval_runtime": 197.0364,
+    "eval_samples": 10715,
+    "eval_samples_per_second": 54.381,
+    "eval_steps_per_second": 2.269
+}
 ```