pitehu/

T5_NER_CONLL_ENTITYREPLACE

This is a T5 small model finetuned on CoNLL-2003 dataset for named entity recognition (NER).

Example Input and Output: “Recognize all the named entities in this sequence (replace named entities with one of [PER], [ORG], [LOC], [MISC]): When Alice visited New York” → “When PER visited LOC LOC"

Evaluation Result:

% of match (for comparison with ExT5: https://arxiv.org/pdf/2111.10952.pdf):

There are some outputs (212/3453 or 6.14% that does not have the same length as the input)

F1 score on testing set of those with matching length :

**Caveat: The testing set of these aren't the same, due to matching length issue... T5_NER_CONLL_OUTPUTLIST only has 27/3453 missing length (only 0.78%); The BERT number is directly from their paper (https://arxiv.org/pdf/1810.04805.pdf)