Closed man0007 closed 4 years ago
I have created my own sentence "there is a abundance of capital because of good profits" to test the sentiment prediction for the fine-tuned model using the notebook given: "FinBert Model Example.ipynb".
When I ran for the first time I got the result as 'positive': https://prnt.sc/vf3fnb When I ran for the second time I got the result as 'neutral': https://prnt.sc/vf3fcr
Why is this variation happening? How can we trust the results from this model if it is not stable?
Thanks for reporting this. There should be model.eval() in the notebook. It's fixed now.
Hi I am facing the same problem. I just commented model.load_state_dict(torch.load(fine_tuned_weight_path)) ...
I have created my own sentence "there is a abundance of capital because of good profits" to test the sentiment prediction for the fine-tuned model using the notebook given: "FinBert Model Example.ipynb".
When I ran for the first time I got the result as 'positive': https://prnt.sc/vf3fnb When I ran for the second time I got the result as 'neutral': https://prnt.sc/vf3fcr
Why is this variation happening? How can we trust the results from this model if it is not stable?