Link to uncased model
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README.md
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [acronym_identification](https://huggingface.co/datasets/acronym_identification) dataset. In particular, this SpanMarker model uses [bert-base-cased](https://huggingface.co/bert-base-cased) as the underlying encoder. See [train.py](train.py) for the training script.
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## Metrics
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It achieves the following results on the validation set:
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [acronym_identification](https://huggingface.co/datasets/acronym_identification) dataset. In particular, this SpanMarker model uses [bert-base-cased](https://huggingface.co/bert-base-cased) as the underlying encoder. See [train.py](train.py) for the training script.
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Is your data not (always) capitalized correctly? Then consider using the uncased variant of this model instead for better performance:
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[tomaarsen/span-marker-bert-base-uncased-acronyms](https://huggingface.co/tomaarsen/span-marker-bert-base-uncased-acronyms).
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## Metrics
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It achieves the following results on the validation set:
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