diff --git a/training.py b/training.py
index 69b5fe5..8925936 100644
--- a/training.py
+++ b/training.py
@@ -18,7 +18,7 @@ if __name__ == '__main__':
     parser.add_argument('--batch-size', type=int, default=10, metavar='S')
     parser.add_argument('--n_workers', type=int, default=4, metavar='S')
     parser.add_argument('--adapter_size', type=int,
-                        default=8, metavar='S')
+                        default=64, metavar='S')
     parser.add_argument('--num-threads', type=int, default=4,
                         help='num threads (default: 4)')
     parser.add_argument('--dropout', type=float, default=0.4, metavar='D',
@@ -47,8 +47,8 @@ if __name__ == '__main__':
 
     train_dataset = TokenizedDataFrameDataset(tokenizer, file_path=args.train_file)
     val_dataset = TokenizedDataFrameDataset(tokenizer, file_path=args.train_file)
-    train_dataset.df = train_dataset.df.iloc[:-1000]
-    val_dataset.df = val_dataset.df.iloc[-1000:]
+    train_dataset.df = train_dataset.df.iloc[:int(len(train_dataset) * 0.9)]
+    val_dataset.df = val_dataset.df.iloc[int(len(train_dataset) * 0.9):]
     test_dataset = TokenizedDataFrameDataset(tokenizer, file_path=args.test_file)
 
     train_loader = DataLoader(train_dataset, shuffle=True, batch_size=args.batch_size,
@@ -62,11 +62,12 @@ if __name__ == '__main__':
 
     config = AdapterConfig(
         hidden_size=768, adapter_size=args.adapter_size,
-        adapter_act='relu', adapter_initializer_range=0.1
+        adapter_act='relu', adapter_initializer_range=1e-2
     )
     model = add_adapters(model, config)
 
-    model = ClassificationModel(model, n_labels=len(train_dataset.y_labels), dropout_prob=0.3)
+    model = ClassificationModel(model, n_labels=len(train_dataset.y_labels),
+                                dropout_prob=0.0)
 
     model.eval()
     model.to(device)