Tried using kaggle’s P100, but I am getting the same error, i.e.
OutOfMemoryError: CUDA out of memory. Tried to allocate 384.00 MiB (GPU 0; 15.90 GiB total capacity; 14.70 GiB already allocated; 245.75 MiB free; 14.78 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Any advice on using another model for sequence classification task rather than xlm?