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--- |
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language: |
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- en |
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license: "apache-2.0" |
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datasets: |
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- CoNLL-2003 |
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metrics: |
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- F1 |
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--- |
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This is a T5 small model finetuned on CoNLL-2003 dataset for named entity recognition (NER). |
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Example Input and Output: |
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“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" |
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Evaluation Result: |
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% of match (for comparison with ExT5: https://arxiv.org/pdf/2111.10952.pdf): |
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| Model| ExT5_{Base} | This Model | T5_NER_CONLL_OUTPUTLIST |
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| :---: | :---: | :---: | :---: | |
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| % of Complete Match| 86.53 | 79.03 | TBA| |
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There are some outputs (212/3453 or 6.14% that does not have the same length as the input) |
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F1 score on testing set of those with matching length : |
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| Model | This Model | T5_NER_CONLL_OUTPUTLIST | BERTbase |
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| :---: | :---: | :---: | :---: | |
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| F1| 0.8901 | 0.8691| 0.9240 |
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**Caveat: The testing set of these aren't the same, due to matching length issue... |
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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) |
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