Hey Folks,
I am attempting to convert a RobertaForSequenceClassification pytorch model (fine tuned for classification from distilroberta-base) to ONNX using transformers 4.9.2. When using the transformers.onnx package, the classifier seems to be lost:
Some weights of the model checkpoint at {} were not used when initializing RobertaModel: ['classifier.dense.bias', 'classifier.out_proj.bias', 'classifier.out_proj.weight', 'classifier.dense.weight']
- This IS expected if you are initializing RobertaModel 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 RobertaModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).

When I specify a feature (–feature sequence-classification) I get an error stating only default is supported. However, when I revert to the convert_graph_to_onnx script that the documentation says is being deprecated, I am able to convert successfully using the --pipeline sentiment-analysis flag.
Is this expected? Does transformers.onnx not support RobertaForSequenceClassification yet, or am I missing some step?