Fix OutOfMemoryError

✅ Solution

OutOfMemoryError in PyTorch usually means your GPU ran out of memory during computation, especially with large models or batches. To fix it, reduce the batch size, simplify the model architecture, use gradient accumulation, enable mixed-precision training (torch.cuda.amp), or move computations to CPU if GPU memory is critically low. Consider using `torch.cuda.empty_cache()` to free unused GPU memory.