Update README.md

README.md

@@ -69,6 +69,30 @@ pipe(do_closed_qa(test_article, question), max_new_tokens=128, temperature=0)[0]
 
 # Training details
 
+We trained using the following three minimalistic prompt templates for the three tasks in STX:
+
+* SNOW
+  ```
+  f"""元の日本語：
+  {original_ja}
+
+  シンプルな日本語："""
+  ```
+* TyDiQA
+  ```
+  f"""{passage_text}
+
+  {question_text}"""
+  ```
+  ```
+* XLSum
+  ```
+  f"""記事：
+  {original_ja}
+
+  要約："""
+  ```
+
 This model was trained for 1000 steps (1.2 epochs) with the model being evaluated every 50 steps. We then chose the best model from these evaluations based on validation loss.
 We used the [qlora](https://github.com/artidoro/qlora) package from artidoro.
 We trained with the following hyperparameters: