runtime error

Some weights of AlbertForSequenceClassification were not initialized from the model checkpoint at ./albert_base_chinese and are newly initialized: ['classifier.weight', 'classifier.bias', 'albert.pooler.bias', 'albert.pooler.weight'] You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference. Traceback (most recent call last): File "/home/user/app/app.py", line 4, in <module> from albert_pred import predict_text File "/home/user/app/albert_pred.py", line 37, in <module> model.load_state_dict(torch.load('./output/best_model.bin', map_location=torch.device('cpu'))) File "/home/user/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1497, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for AlbertForSequenceClassification: Unexpected key(s) in state_dict: "albert.embeddings.position_ids".

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