Add version print for transformers to debug dependency issues

requirements.txt

@@ -1,5 +1,5 @@
 torch>=2.2.0
-transformers>=4.40.0
+transformers==4.40.0
 scikit-learn
 pandas
 numpy<2

train_abuse_model.py

@@ -6,16 +6,18 @@ import os
 import pandas as pd
 import numpy as np
 import torch
+from torch.utils.data import Dataset
+
+print("PyTorch version:", torch.__version__)
 
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import classification_report, precision_recall_fscore_support
 
-from torch.utils.data import Dataset
-
 # Hugging Face Hub
 from huggingface_hub import hf_hub_download
 
 # Hugging Face transformers
+import transformers
 from transformers import (
     AutoTokenizer,
     DebertaV2Tokenizer,
@@ -25,7 +27,8 @@ from transformers import (
     Trainer,
     TrainingArguments
 )
-
+# Check versions
+print("Transformers version:", transformers.__version__)
 
 # Check for GPU availability
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")