Hi @nsingh, without seeing your code it’s hard to know exactly what’s going wrong but based on this comment

We get the correct dimension, however, we get values between about -3.04 and 7.14 (unsure what these values refer to).

my guess is that you are getting the logits from the model instead of the predicted classes. I ran into this problem recently and the solution was to specify pipeline_name=sentiment-analysis to load the model for a TextClassificationPipeline:
from transformers.convert_graph_to_onnx import convert

model_ckpt = ...
tokenizer = ...
onnx_model_path = ...
convert(framework="pt", model=model_ckpt, tokenizer=tokenizer,
 output=onnx_model_path, opset=12, pipeline_name="sentiment-analysis")

By default, convert_graph_to_onnx uses the feature-extraction pipeline which might explain why you’re seeing negative numbers (i.e. the logits)