pandeydivesh15 / ner-using-deep-learning Goto Github PK

For the English data sets, loss is nan since training starts. I tried to match the Keras and tensorflow versions (except that I use CPU), but it doesn't help. I also tried different datasets or optimizer, none of them helps. Can you please share some thoughts on troubleshooting?

FYI, every output looks the same before m.train(epochs=10) in the "NER-using-Deep-Learning" notebook.

The NER corpus include many more 'O' label than any entities.
How can we fix this using keras?
I tried sample_weight to ajust the loss function during training, but it does not appear to fix the problem fully. What would you suggest?
Thx

what is format of datset required for your NER . I wnat to use on my data set which is in SSF fromat.
kindly help me for that.

Hello,u haven't mentioned the type of decoding that has to happen in process_data.py in the method read_data and i have tried with utf-8 but it is still showing the same error. It would be a great help if u looked into this. I have attached a screenshot of the error.