Update README.md

README.md

@@ -2,12 +2,30 @@
 license: apache-2.0
 base_model: albert-base-v2
 tags:
-- generated_from_trainer
+  - generated_from_trainer
 datasets:
-- squad
+  - squad
 model-index:
-- name: albert-base-v2-finetuned-squad
-  results: []
+  - name: albert-base-v2-finetuned-squad
+    results:
+      - task:
+          name: Question Answering
+          type: question-answering
+        dataset:
+          type: squad_v2
+          name: The Stanford Question Answering Dataset
+          args: en
+        metrics:
+          - type: eval_exact
+            value: 76.263
+          - type: eval_f1
+            value: 84.734
+language:
+  - en
+metrics:
+  - exact_match
+  - f1
+
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,10 +36,12 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the squad dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.4539
+- Exact Match: 80.60548722800378
+- F1 score: 88.76870326468953
 
 ## Model description
 
-More information needed
+This model is fine-tuned on the extractive question answering task -- The Stanford Question Answering Dataset -- SQuAD2.0.
 
 ## Intended uses & limitations
 
@@ -29,7 +49,7 @@ More information needed
 
 ## Training and evaluation data
 
-More information needed
+Training and evaluation was done on SQuAD2.0.
 
 ## Training procedure
 
@@ -60,4 +80,4 @@ The following hyperparameters were used during training:
 - Transformers 4.34.0
 - Pytorch 1.12.1
 - Datasets 2.14.5
-- Tokenizers 0.14.1
+- Tokenizers 0.14.1