RuntimeError: Error(s) in loading state_dict for BertForTokenClassification:

[knightperfectionist]

from bert_deid.model import Transformer

# load in a trained model
model_path = 'bert_deid_model'
deid_model = Transformer(model_path)

with open('tests/example_note.txt', 'r') as fp:
    text = ''.join(fp.readlines())

print(deid_model.apply(text, repl='___'))

I am using above snippet of code and providing model path as pre-trained model path.

Getting the following error

RuntimeError: Error(s) in loading state_dict for BertForTokenClassification:
	size mismatch for classifier.weight: copying a param with shape torch.Size([25, 1024]) from checkpoint, the shape in current model is torch.Size([2, 1024]).
	size mismatch for classifier.bias: copying a param with shape torch.Size([25]) from checkpoint, the shape in current model is torch.Size([2]).

@alistairewj

[alistairewj]

Weird.. what is the md5sum of the downloaded model files?