From 5df9e402bd964b101eb809d6d3b438f3029a7d79 Mon Sep 17 00:00:00 2001
From: BJH9 <tfzangin9@gmail.com>
Date: Wed, 10 Jan 2024 22:50:24 +0000
Subject: [PATCH] =?UTF-8?q?[exp]:=20=EB=8D=B0=EC=9D=B4=ED=84=B0=20?=
 =?UTF-8?q?=EA=B0=95=ED=99=94=20=EC=8B=A4=ED=97=98=20#28?=
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---
 code/inference.py | 4 ++--
 code/train.py     | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/code/inference.py b/code/inference.py
index 1070a36..4db7264 100644
--- a/code/inference.py
+++ b/code/inference.py
@@ -96,7 +96,7 @@ def main(args):
   # 아래 directory와 columns의 형태는 지켜주시기 바랍니다.
   output = pd.DataFrame({'id' : test_dataset['id'],'pred_label':pred_answer,'probs':output_prob,})
 
-  output.to_csv('./prediction/submission.csv', index=False) # 최종적으로 완성된 예측한 라벨 csv 파일 형태로 저장.
+  output.to_csv('./prediction/augment_2.csv', index=False) # 최종적으로 완성된 예측한 라벨 csv 파일 형태로 저장.
   #### 필수!! ##############################################
   print('---- Finish! ----')
 
@@ -105,7 +105,7 @@ def main(args):
     parser = argparse.ArgumentParser()
     
     # model dir
-    parser.add_argument('--model_path', type=str, default="./best_model/bestmodel.pth")
+    parser.add_argument('--model_path', type=str, default="./best_model/augment2_bestmodel.pth")
     args = parser.parse_args()
     print(args)
     main(args)
diff --git a/code/train.py b/code/train.py
index 52e3b80..6a9e4ea 100644
--- a/code/train.py
+++ b/code/train.py
@@ -20,7 +20,7 @@ def train():
     
     # MODEL_NAME = "bert-base-uncased"
     MODEL_NAME = "klue/roberta-large"
-    TRAIN_PATH = "../dataset/train/augmented_train1.csv"
+    TRAIN_PATH = "../dataset/train/augmented_train2.csv"
     LABEL_CNT = 30
     P_CONFIG = {'prompt_kind' : 's_and_o',  # ['s_sep_o', 's_and_o', 'quiz']
                 'preprocess_method' : 'typed_entity_marker_punct', # ['baseline_preprocessor', 'entity_mask', 'entity_marker', 'entity_marker_punct', 'typed_entity_marker', 'typed_entity_marker_punct']
@@ -104,7 +104,7 @@ def train():
     trainer.train()
     # git에 올린 코드
     model_state_dict = model.state_dict()
-    torch.save({'model_state_dict' : model_state_dict}, './best_model/augment1_bestmodel.pth')
+    torch.save({'model_state_dict' : model_state_dict}, './best_model/augment2_bestmodel.pth')
     
 def main():
     train()