Prediction on GLUE, COLA dataset
Hi,I tried to finetune ‘bert-base-cased’ on COLA task on GLUE dataset.The training was OK, but I got the following problem when I performed prediction on ‘test’ split using the following code:predictions = trainer.predict(test_split)I got the following errors:…/aten/src/ATen/native/cuda/Loss.cu:257: nll_loss_forward_reduce_cuda_kernel_2d: block: [0,0,0], thread: [0,0,0] Assertiont >= 0 && t < n_classesfailed.…/aten/src/ATen/native/cuda/Loss.cu:257: nll_loss_forward_reduce_cuda_kernel_2d: block: [0,0,0], thread: [1,0,0] Assertiont >= 0 && t < n_classesfailed.…/aten/src/ATen/native/cuda/Loss.cu:257: nll_loss_forward_reduce_cuda_kernel_2d: block: [0,0,0], thread: [2,0,0] Assertiont >= 0 && t < n_classesfailed.…RuntimeError: CUDA error: device-side assert triggeredIf I changed the prediction to ‘validation’ split, everything will be OK.The questions areIs this a known bug?Are there a good method to check where this problem come from?I have seen that for this dataset (GLUE, COLA), the ‘label’ provided in ‘test’ split differs from the label in ‘train’ and ‘validation’ splits. Do I need to modify these labels before evaluating the model?Thanks.