Funetuning Longt5 Parameters which did not receive grad during training
I am trying to use longt5 for summarizing taskI am using thisscriptand thismodelI am getting this errorTraceback (most recent call last):File “/cephfs/home/arij/Memory-transformer-with-hierarchical-attention_MLM/Summarization/run_summarization_notrainer-Copy1.py”, line 947, inmain()File “/cephfs/home/arij/Summarization/run_summarization_notrainer-Copy1.py”, line 821, in mainoutputs = model(**batch)File “/home/arij/anaconda3/envs/lib/python3.9/site-packages/torch/nn/modules/module.py”, line 1190, in _call_implreturn forward_call(*input, **kwargs)File “/home/arij/anaconda3/envs/lib/python3.9/site-packages/torch/nn/parallel/distributed.py”, line 1026, in forwardif torch.is_grad_enabled() and self.reducer._rebuild_buckets():RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by passing the keyword argumentfind_unused_parameters=Truetotorch.nn.parallel.DistributedDataParallel, and bymaking sure allforwardfunction outputs participate in calculating loss.If you already have done the above, then the distributed data parallel module wasn’t able to locate the output tensors in the return value of your module’sforwardfunction. Please include the loss function and the structure of the return value offorwardof your module when reporting this issue (e.g. list, dict, iterable).Parameters which did not receive grad for rank 1: encoder.block.0.layer.0.TransientGlobalSelfAttention.global_relative_attention_bias.weightParameter indices which did not receive grad for rank 1: 6