chore(debug): move device check to top of script for clearer startup logs

train_abuse_model.py

@@ -8,10 +8,6 @@ import numpy as np
 import torch
 from torch.utils.data import Dataset
 
-print("torch.cuda.is_available():", torch.cuda.is_available())
-print("Using device:", device)
-print("PyTorch version:", torch.__version__)
-
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import classification_report, precision_recall_fscore_support
 
@@ -34,8 +30,12 @@ print("Transformers version:", transformers.__version__)
 
 # Check for GPU availability
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+print("torch.cuda.is_available():", torch.cuda.is_available())
+print("Using device:", device)
+print("PyTorch version:", torch.__version__)
 
 # Custom Dataset class
+
 class AbuseDataset(Dataset):
     def __init__(self, texts, labels):
         self.encodings = tokenizer(texts, truncation=True, padding=True, max_length=512)