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License: MIT License
The tokens returned by Spacy should still be converted into distributed representations to be easily usable by a DL model. For the baseline, do we encode the question with the Universal Sentence Encoder and use a SOTA word embedding for the context? Which word embedding is still very popular? (Fastext, Glove, ?) Also, some researchers use Pair Byte Encoding (PBE) to encode information at the sub-word level.
In this baseline, we will use fasttext for token word embeddings and universal sentence encoder for questions.
We will have a basic training loop with feedback.
Add a tokenizer for bert with proper unit tests
The JSONL format is described on this page.
Can we use a Python script to do it with request?
From MRQA 2019 Shared Task on Generalization answers are evaluated using exact match and token-level F1 metrics. The mrqa_official_eval.py script is used to evaluate predictions on a given dataset.
Add a method for loading the data into a tf.Dataset.
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