update deberta

DeBERTaV3.py

@@ -34,8 +34,8 @@ class QuestionDataset(Dataset):
 class ModelLoader:
     def __init__(self):
         self.path = "DeBERTaV3/input/"
-        self.train_df = pd.read_csv(self.path + "cleaned_train.csv")
-        self.test_df = pd.read_csv(self.path + "cleaned_test.csv")
+        self.train_df = pd.read_csv(self.path + "train.csv")
+        self.test_df = pd.read_csv(self.path + "test.csv")
 
         self.tokenizer = AutoTokenizer.from_pretrained('microsoft/deberta-v3-base')
         self.df = self.train_df
@@ -87,11 +87,11 @@ class ModelLoader:
                              metrics=[accuracy, F1Score()]).to_fp16()
         try:
             # First attempt: Try loading with weights_only=True
-            self.learn.load('fastai_QIQC-deberta-v3', strict=False, weights_only=True)
+            self.learn.load('fastai_QIQC-deberta-v3-unclean', strict=False, weights_only=True)
         except Exception as e:
             print(f"Warning: Could not load with weights_only=True. Falling back to default loading. Error: {e}")
             # Second attempt: Fall back to regular loading if the first attempt fails
-            self.learn.load('fastai_QIQC-deberta-v3', strict=False)
+            self.learn.load('fastai_QIQC-deberta-v3-unclean', strict=False)
 
     def get_learner(self):
         return self.learn

DeBERTaV3/input/test.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:01169d7400285f1e5f1c155f1e07d87d5c15ca21e265bc0092a943eefc47f419
+size 35011536

DeBERTaV3/input/train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b8549942872d29c9eeb9778762a51d122e12a4e61d1e657cd9cd275a403b415
+size 124206772