Evaluation in question answering tasks can be tricky as it’s hard to convert the model output to answers in the original contexts. This video will (hopefully) make everything clearer!
This video is part of the Hugging Face course: http://huggingface.co/course
Open in colab to run the code samples:
https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/videos/qa_postprocessing_tf.ipynb
PyTorch version: https://youtu.be/BNy08iIWVJM
Related videos:
– Data processing for Question Answering: https://youtu.be/qgaM0weJHpA
– Inside the Question answering pipeline: https://youtu.be/b3u8RzBCX9Y
– Fast tokenizer superpowers: https://youtu.be/3umI3tm27Vw
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