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quoref metric and evaluator #3153
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pdasigi
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@matt-gardner this is ready to be reviewed. Should be pretty straightforward as the quoref metric depends heavily on the drop metric, with just the data formats being different. I think this is the last needed piece for the leaderboard. |
| answers_dict[query_id] = candidate_answers | ||
| return answers_dict | ||
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| def evaluate_json(annotations: Dict[str, Any], predicted_answers: Dict[str, Any]) -> Tuple[float, float]: |
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Why can't you use the drop script for this function (and the one above) also?
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Quoref's json format is the same as that of SQuAD, and DROP's is different. So evaluate_json needs to be different, and evaluate_prediction_file calls that function, so that needed to be rewritten as well. Mentioned this in the docstring.
matt-gardner
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Aug 21, 2019
| @@ -26,3 +26,4 @@ | |||
| from allennlp.training.metrics.srl_eval_scorer import SrlEvalScorer, DEFAULT_SRL_EVAL_PATH | |||
| from allennlp.training.metrics.unigram_recall import UnigramRecall | |||
| from allennlp.training.metrics.auc import Auc | |||
| from allennlp.training.metrics.quoref_em_and_f1 import QuorefEmAndF1 | |||
reiyw
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Nov 12, 2019
* quoref metric and evaluator * added tests and sample data files * missing prediction * take predictions in simple format too * added a test and fixed docs * test running as a script * removed metric file for quore and added more comments * removed old import
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