Training emotions data with bert model
I am creating a emotions detection model on distilbert_base_uncased model, using my own dataset, that contains the data as format text, label where label=emotions, like happy, sad, angryI tried different training method, but did not succeeded, can any one tell how to train the model.Also I checked this notebook from@bhadresh-savani:UnderstandingNLP/go_emotion_of_transformers_multilabel_text_classification_v2.ipynb at master · bhadreshpsavani/UnderstandingNLP · GitHubbut the problem is that the data it has contains the labels in array format, eg: [0,0,0,1,0…]but my labels are direct: eg: happy, sad, angryso it is having conflicted and I can not able to train the model.@bhadresh-savaniif you have any idea and can give me what change I would do to make it work my data that will be really helpful!