Hello I'm running the code in my dataset. With frozen weights the values are promising.
However, to fully defrost the BERT the model hits only one label.
Warning: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use zero_division parameter to control this behavior. warn_prf(average, modifier, msg_start, len(result))
Hello I'm running the code in my dataset. With frozen weights the values are promising.
However, to fully defrost the BERT the model hits only one label.
Warning: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use
zero_division
parameter to control this behavior. warn_prf(average, modifier, msg_start, len(result))macro avg 0.20 0.50 0.29 70 weighted avg 0.16 0.40 0.23 70
Do you need any more procedures for the model to learn labels correctly? I'm using 470 examples.