No, just use very few samples (e.g. select 10 samples from your dataset) and run the code.
If your model cannot overfit these 10 samples perfectly (loss converges towards zero, accuracy towards 100%), then there might be another bug in the code or e.g. the hyperparameters, model architecture, etc. might not be working in your use case. This would be a good base for debugging the issue and make sure your model can overfit a small data sample before digging further into the code.