thanks for your answer,
the code is the same

actually no, the warning messages have been changed in two cases:


in converting dataset to features I used to get the the below message for more times while now I receive it just for one time

‘’ Token indices sequence length is longer than the specified maximum sequence length for this model (513 > 512). Running this sequence through the model will result in indexing errors’’

about the parameters also the previous warning was this:
‘’ Some weights of the model checkpoint at roberta-base were not used when initializing ROBERTA: [‘lm_head’] - This IS expected if you are initializing ROBERTA from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPretraining model). - This IS NOT expected if you are initializing ROBERTA from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). All the weights of ROBERTA were initialized from the model checkpoint at roberta-base.’’

( but I searched the new warning and noticed that as long as I am using the embedding of the first token this warning is not important.)


data is the same


due to the changes in the warning messages it seems like that the version of transformers has been changed, but I do not know what was the version before, and now when I try it with a lower version, I still get the same output


I do not know, but I can check


the loss function used to start from 0.20 and decrease at least 0.02 per epoch, and the model used to converge to zero loss value


yes I have a notebook which was trained in October 15th and everything was ok with that
( I can share it if you need)


The colab env in both cases is GPU


I do not know the exact time, but I am sure that it was working well until October 15